PhD research projects

The UTU-GreDiT provides interdisciplinary PhD projects related to the EU’s framework of the Green and Digital Transition, namely: 1. Rescuing biodiversity to safeguard life on Earth; 2. Farm to Fork; 3. Circular bio-based Europe; 4. Water security for the planet; 5. Globally competitive space systems; 6. People-centric sustainable built environment; 7. Clean Hydrogen and 8. One health. Each PhD project is associated with experienced research group(s) and secondment position(s). Research groups of the UTU-GreDiT include expertise from biodiversity research, biochemistry, biology, geography, geology, computer science, information and communication technology, management and organisation, materials engineering, molecular plant biology, sustainable biotechnological processes. Information related to the PhD project, e. g. secondment positions might be changed or completed in the future.

The UTU-GreDiT PhD projects

Background:	Sustainable river management and conservation requires systemic understanding of the whole watershed. Sediment connectivity, describing the dynamic interactions of sediments between different parts of the system, is directly linked to the geomorphology and hydrology of the river basins and has a key role in the watershed nutrient dynamics. New methodological approaches are required to investigate the sediment connectivity in such spatial and temporal resolution that facilitate decision making and green transition in river management. In the Freshwater Competence Centre, we deploy and further develop the state-of-the art digital technologies, tools and digital twin approaches to increase the understanding of sediment connectivity and the functioning of the river basins and riverine ecosystems in order to support the green transition in water management.
PhD project description:	We are seeking a talented doctoral researcher with good knowledge on fluvial studies including remote sensing, hydraulic modelling and fluvial morphology. The PhD project aims at sustainable and resilient river management by the means of digitalisation and state-of-the-art instrumentations. Main objective of the project is to study sediment connectivity of the river basins, and measure, model and project river channel processes in order to develop and support digital and green transition in river basin management. We assess impacts of green transition and climate change on water resources considering “in parallel” hydro-morphodynamic and land cover changes occurring within the river basins. The doctoral researcher will carry out scientific research together with the multi-disciplinary research group of the Freshwater Competence Centre. PhD researcher will focus on the river systems in the boreal-subarctic region. They will undertake the following studies in the PhD thesis: 1) the river mapping and measurements with laser scanning, sonar and acoustic doppler current profiler on the field and 2) apply computational modelling approach to study how climate change and the related flooding and droughts will affect the future river systems in those areas; 3) analysis of connectivity and controls of the processes now and in the future, considering the climate change effects. The doctoral researcher will collect field data on boreal-subarctic catchments by applying the state-of-the-art in-situ measurement techniques, process the data, build computational models, and use those to analyse the river systems.
Specific requirements:	The position requires an active approach, diligence and cooperation skills, willingness to work as a part of a team and a passion to learn new. We also expect a Master’s degree in, for example, physical geography, water engineering, hydrology, or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) Knowledge and interest on Geo-ICT approaches; (2) Strong understanding on hydrological systems or fluvial processes; (3) Interest and experience in outdoors & field work; (4) Experience in computational modelling, spatio-statistical approaches and/or programming.
Secondment:	Finnish Geospatial Research Institute (FGI) and/or University of Oulu (Finland) and/or IISD Experimental Lakes Area (Canada)
Dept./Faculty to which the thesis belongs	Department of Geography and Geology/ Faculty of Science
Principal supervisor / Project web page	Prof. Petteri Alho, UTU https://sites.utu.fi/fcrg/

Background:	The accelerating climate change together with the global population growth put major pressure on the fresh waters worldwide. Understanding the river basin-human system is thus essential in fostering sustainable and nature-based river management practices and in climate change adaptation. Further insights on how rivers respond to climate change and anthropogenic activities are highly needed. By utilizing the recent advancements of the geospatial data, (cost-) efficient survey technologies, and data processing and modelling environments, it is possible to study these phenomena in higher detail and extent than ever and direct the water management to more sustainable direction.
PhD project description:	We are looking for a talented and motivated PhD student with a background in geography, hydrology, civil engineering or a relevant field to study catchment scale hydrology and water management. The PhD project aims at catchment scale hydro-morphological analysis of Boreal and Sub-Arctic catchments which have warmed considerably faster than the global average and where the snow and ice conditions, flow regime and erosional processes have already experienced a notable change. The main objective of the project is to increase our understanding on how the changing climate and anthropogenic activities, together with land cover characteristics affect the hydrological and morphological processes in Boreal and Sub-Arctic catchments and what kinds of water management measures should be applied to mitigate climate change effects. Methodological approaches will contain field measurements with state-of-the-art instrumentation, remote sensing and geo-ICT methods combined with computational modeling. Doctoral researcher will 1) combine open remote sensing data and field-based data over the catchments to capture the relevant anthropogenic activities and environmental properties. They will collect field data by applying the state-of-the-art in-situ measurement techniques and stakeholder collaboration. The doctoral researcher will apply the data to 2) model the climate change and anthropogenic impacts on water resources in river basin scale and 3) assess relevant water management measures. The project and the field measurements will be implemented in close cooperation with the multi-disciplinary research group of the Freshwater Competence Centre and relevant stakeholders. The applicant will gain all the required support, field instrumentation and supervision from the experienced research team.
Specific requirements:	The applicant should be active, motivated and self-guided and have initiative and willingness for team working. We also expect a Master’s degree in, for example, physical geography, water engineering, hydrology, or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) Knowledge and interest on Geo-ICT approaches and remote sensing; (2) Strong understanding on hydrological processes; (3) Interest and experience in outdoors & field work. Experience in computational modelling, spatio-statistical approaches and/or programming are for great advantage.
Secondment:	Finnish Environment Institute (SYKE) and/or University of Oulu (Finland)
Dept./Faculty to which the thesis belongs	Department of Geography and Geology/ Faculty of Science
Principal supervisor / Project web page	Elina Kasvi, UTU, emkasv@utu.fi https://sites.utu.fi/fcrg/

This research project is a Cotutelle PhD project between University of Turku, Finland and University of Lund, Sweden. Cotutelle – also known as joint doctoral supervision – concerns an arrangement where a doctoral researcher pursues a doctoral degree at two separate universities or other institutions of higher education in two different countries. The doctoral researcher works on their doctoral dissertation equally in both universities. The objective of a Cotutelle agreement is that the researcher receives a degree from both universities but completes only one doctoral dissertation.

Background:	Urban areas are particularly vulnerable to climate change impacts, such as increased heat waves and other extreme weather events, due to their reduced capacity for heat mitigation and water absorption, which challenges the infrastructure, living conditions and biodiversity in the cities. Innovative and sustainable measures, aiming to increase the resilience of urban areas to climate change impacts are thus urgently needed. Nature-based solutions (NBS) leverage the natural environment to address environmental and societal challenges and are increasingly used in urban stormwater management as decentralised measures, combining different green and blue infrastructures. They are considered as a sustainable way of climate change adaptation enabling flood and drought reduction and heat wave mitigation, with additional benefits related to human well-being and biodiversity. Nature-based solutions affect urban hydrology in different ways through runoff detention, infiltration, evapotranspiration, interception, and slow conveyance and discharge. However, to be able to apply NBS in the most efficient and sustainable way, more insights, on the effectiveness of their combined use in urban areas related to different weather scenarios, are needed.
PhD project description:	We are seeking a talented doctoral student with good knowledge of stormwater management and urban hydrology. This PhD project aims to increase our understanding of sustainable and resilient climate adaptation of urban areas by assessing the efficiency and climate adaptation capabilities of Natural-based solutions (NBS) in stormwater management in Nordic cities during the extreme weather conditions they are facing. The main objectives are to study how extreme weather scenarios will affect Nordic urban areas and the potential of NBSs in tackling the emerging stormwater management challenges and mitigating the climate change effects (such as floods, droughts and heat waves). The project will involve collaboration between Turku and Lund Universities, facilitating the exchange of knowledge and data. The PhD researcher will focus on comparative studies conducted in Nordic cities to explore how NBS can be applied in different urban settings while considering climate change. They will undertake the following studies in the PhD thesis: 1) Efficiency Modelling for NBS: Monitoring and modelling the efficiency of NBS, including adaptability for upscaling. Data collection from various NBS, with probes measuring water-related parameters, and assessment through modelling and calculations. 2) Development of Extreme Weather Scenarios: Creating extreme weather scenarios to assess NBS resilience and performance. These scenarios are based on historical climate data and climate change projections. 3) Modelling Hydrology During Extreme Weather Scenarios: Building a hydrological model using data from Study 1 and the extreme weather scenarios from Study 2 to evaluate the climate adaptation capability of NBS. The candidate will be involved in data collection, modelling, and analysis, aiding in the development of innovative strategies to address climate challenges in Nordic cities.
Specific requirements:	The applicant should be motivated and self-guided and have initiative and willingness for international teamwork. We also expect a master’s degree in, for example, physical geography, water engineering, environmental engineering, hydrology, or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) Knowledge and interest in stormwater management and urban hydrology; (2) Strong understanding of hydrological processes; Experience in computational modelling and statistics are of great advantage.
Secondment:	City of Turku and the Turku University of Applied Sciences
Dept./Faculty to which the thesis belongs	Department of Geography and Geology/ Faculty of Science COTUTELLE: Department of Building and Environmental Technology/ Faculty of Engineering/ Lund University
Principal supervisor / Project web page	Dr. Elina Kasvi, UTU, emkasv@utu.fi https://sites.utu.fi/fcrg/
2nd supervisor	Dr. Johanna Sörensen, LU

Background:	Our team runs one of the world’s longest research project about pollution-related effects on wild birds. Our main study sites locate in Harjavalta area, SW Finland, ca. 100 km from Turku University, where we work. This area has been one of the most polluted locations in Finland since 1940’s, when the local copper-nickel smelter started operating. The main pollutants in the area include heavy metals (e.g. Cu, Ni, Pb, Cd, As) and sulfuric dioxides. Later on, especially in 1990’s improved cleaning technologies have drastically cut down the emissions and, thanks to our long-term research, we have been able to witness relatively fast recovery of bird populations. Our main study species are small insectivorous and cavity breeding birds like the great tit (Parus major), pied flycatcher (Ficedula hypoleuca) and blue tit (Cyanistes caeruleus). To follow the breeding success of these birds we have put up a large number of nest boxes in the polluted area and comparable habitats in less polluted sites further away from the smelter. Aside from Harjavalta, we continuously collaborate with our European colleagues who perform similar studies around various types of polluted sites. Research topics and themes have varied a lot over these years. This project started with some basic ecological questions, like to find out if point-source emissions affected the ectoparasite numbers, breeding success or other fitness parameters of the focal passerine species. Soon it became evident that especially F. hypoleuca suffered from thin and porous egg shells and poorly developing nestling bones (e.g. having soft and bent leg or wing bones). At this point we became interested in bird’s calcium availability and its role in explaining metal toxicity (in general rich Ca in diet diminishes harmful effects of toxic metals). Calcium has since then remained one of our main topics of interest until today and we have also measured many Ca-related physiological parameters from birds, like vitamin D levels. The great tit, on the other hand, did not show corresponding problems with Ca, but instead suffered from relatively high nestling mortality in the polluted area, resembling another tit species, P. caeruleus. Since the growth rate of nestlings was inferior in the polluted environment we started to measure the abundances of their main prey items, caterpillar larvae and other insects. These studies showed that the amount of nutritionally good (e.g. being rich in carotenoids) food was decreased in the polluted area. A series of studies related to carotenoids followed and we found that the lack of some carotenoids (e.g. lutein) affected growth and even the color of bird plumages: the normally yellow plumage of P. major nestlings was paler in the polluted area because of the lack of suitable yellow carotenoid pigments. Since then we have measured the caterpillar abundance in some breeding seasons but these data are not yet analyzed and it would be very interesting to see if the situation has changed along the reduced emissions. Many physiological health-related parameters have been measured from birds over the years. For example, one important mechanism of action by heavy metals is production of oxygen radicals in body, which together with reduced antioxidants (e.g. carotenoids, vitamins and antioxidant enzymes) may cause oxidative stress. We have found signs of oxidative stress in F. hypoleuca and to some extent it seems to be related to shortage in Ca-availability. Likewise, P. major chicks show increased activity of some antioxidant enzymes in the polluted area, although this may rather be explained by their poor growth than direct toxic effect of metals. We have also found some indication of pollution-related epigenetic changes in P. major via DNA methylation. Right now, we are focusing on still one important nutrition related component, bird gut microbiome. So far, we have already found interesting differences among bird species and in relation to pollution levels. Bird nest is an important early-life microbial environment for altricial bird species and microbial community composition (β-diversity) also seem to differ among nests between polluted and control sites. Whether the observed changes in microbiomes are reflected in birds’ fitness, remains to be explored. In the future, we would also like to find out how diet composition is related to the gut microbiome and growth of nestlings and whether metal pollution plays a role in modifying this vital system.
PhD project description:	We are looking for a highly motivated PhD student enthusiastic with environmental ecology and pollution-related environmental problems. Earlier experience with bird-related studies and field work is considered an advantage. Our main study sites are located in the surroundings of a point-source of heavy metal emissions, a copper-nickel smelter in Harjavalta, SW Finland. Breeding populations of insectivorous birds have been studied in this metal polluted area >30 years and we have ample background data and a long time-series available for the new project. The project will be implemented in close cooperation with the main local air pollution source, Boliden Harjavalta company. The thesis will consist of three main studies for which we suggest preliminary topics, but which can be modified as needed. First of them is a literature-based review on bird nutrition-related studies around point-sources of metal pollution, sorting out the current state of knowledge on which kind of growth-related effects, including physiological biomarkers, are common around such emission sources. The second study aims to document the actual dietary changes in a polluted area. This includes working with existing time-series on invertebrate abundance but also collecting new samples and data in the field, e.g. using DNA metabarcoding for identifying pollution-related differences in birds’ food composition. Nutrient contents (lipid, protein and carbohydrate levels) of the main insect prey items will be measured. Such information will be combined with nestling growth and other fitness parameters. The third part of the thesis will explore experimentally the factors affecting the nutritive quality of insects in the polluted environment. For this, some of the birds’ prey items will be exposed to environmentally relevant mixtures of heavy metals to find out possible metal-related changes in insect physiology and nutritive content. Because of field-work periods, driving license is an absolute necessity. This ambitious PhD position offers opportunities for improving skills e.g. in implementing practical environmental field work, laboratory analyses, project management in cooperation with industrial enterprises, data analyses and academic writing. After training, the PhD will be capable of working in the private sector, public sector or academia. Training will take place in 2024-2028 within University of Turku ESR doctoral program Solutions for Green and Digital Transition (UTU-GreDiT), which is a unique European Union COFUND doctoral program that provides an inter-disciplinary, inter-sectoral and international training ecosystem an Early Stage Researcher focusing on Green and Digital Transition in order to strengthen transformative change.
Specific requirements:	The MSc degree should be in the fields of Biology, Environmental Ecology, Conservation Biology or alike. Because of field-work periods, driving license is an absolute necessity.
Secondment:	Boliden Harjavalta Ltd
Dept./Faculty to which the thesis belongs	Department of Biology / Faculty of Science
Principal supervisor / Project web page	Dr. Tapio Eeva, teeva@utu.fi https://sites.utu.fi/birdsandpollution/

Background:	During the last decades, surface waters have become browner throughout the Northern hemisphere. While the reasons for brownification are complex and not well understood, the brownification is having significant consequences to the ecosystem and e.g. declines of aquatic invertebrates have been noted. Brownification might also directly influence the physiology and immune capacity of aquatic organisms and, thus, their vulnerability to diseases. However, so far there is a lack of studies about these aspects.
PhD project description:	Therefore, the project will focus on the ecophysiological responses of different taxa to brownification with particular emphasis on fungal diseases. The thesis will consist of three main studies for which we suggest preliminary topics, but which can be modified as needed. First of them will investigate if the fungal disease saprolegniasis in fish is promoted by brownification. The second will assess if Chytridiomycosis is more likely to occur under brownification conditions, thus increasing the risk of the disease to spread in amphibians (model species include Rana temporaria and Lissotriton vulgaris). The third part will focus on an experiment to assess the ecophysiological response (behavioural, metabolic, and oxydative stress, etc) of fish and amphibians to brownification. Our main study sites are located in the Evo area where surveys on water quality have been collected over 30 years. Impact of brownification is currently studied there on multiple taxa: aquatic invertebrates, amphibians, fish and bird populations. Secondments in ecotoxicology, sediment analyses and machine learning will be organized with NTNU and Nantes university.
Specific requirements:	We are thus looking for a highly motivated PhD student enthusiastic with environmental ecology and water quality-related environmental problems. Earlier experience with aquatic-related studies and lab and experimental work are considered an advantage. Candidates having background about ecotoxicology & physiology, and skills about laboratory measurements, handling animals, and statistical analyses are preferred. This ambitious PhD position will offer opportunities for improving skills e.g. in implementing practical environmental field work, laboratory analyses, project management in cooperation with stakeholders in aquaculture, data analyses and academic writing. After training, the PhD will be capable of working in the private sector, public sector or academia.
Secondment:	Norwegian University of Science and Technology (NTNU) / Nantes University
Dept./Faculty to which the thesis belongs	Department of Biology
Principal supervisor	Prof. Katja Anttila, katja.anttila@utu.fi

PhD project description:	The project aims at identifying the diverse values of nature supporting human and other species wellbeing to enable just multispecies transition in cities. Main objective of the project is to study citizen’s diverse values of nature applying a place-based mixed methods approach in order to support a wider understanding of nature in urban context to promote transformative pathways to sustainability in green infrastructure planning. The window for avoiding irreversible impacts of biodiversity loss on people and nature is rapidly closing. To overcome this, we need to more effectively consider green infrastructure planning to promote biodiversity also in cities, aiming for mutual wellbeing of people and other species. The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) published a typology on valuation of nature, indicating how different ways of living in the world shape instrumental, intrinsic and relational values, and has potential to represent both human and other species in green infrastructure planning. The aim of this doctoral project is to operationalise the IPBES Values Typology to develop a new spatial approach to elicit the distribution of human instrumental and relational values and other species intrinsic values, and the interconnections among them. The doctoral researcher will apply a place-based mixed methods approach to study people’s values on nature through participatory mapping, qualitative, and geospatial approaches. The research aims to produce relevant knowledge and promote multispecies perspective in spatial planning to support sustainability transformations in cities. The research requires close collaboration citizens, planners, and other relevant stakeholders. The specific study context will be considered with the doctoral researcher and the supervisors. The doctoral researcher will carry out the research in the interdisciplinary Sustainable Landscape Systems Research Group (https://sites.utu.fi/landscape/). The doctoral project connects tightly to the Research Council of Finland funded project Multispecies transition of cities and regions (MUST).
Specific requirements:	We are seeking for a talented doctoral researcher with good knowledge of human-nature interactions, socio-ecological systems and resilience, urban green infrastructure, and with an interest in diverse methods for the valuation of nature. The position requires an active approach, diligence and cooperation skills, willingness to team work, and a passion to learn new methods and perspectives. We expect a Master’s degree in, human geography, landscape planning, urban studies, or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) strong understanding on human-nature interactions, socio-ecological systems and resilience, (2) interest and experience in studying human-nature connections, (3) knowledge and interest in performing mixed methods research.
Secondment:	Mapita Ltd.
Dept./Faculty to which the thesis belongs	Department of Geography and Geology/ Faculty of Science
Principal supervisor / Project web page	Nora Fagerholm, ncfage@utu.fi https://sites.utu.fi/landscape

Background:	Regenerative business entails firms moving beyond sustainability risk management and harm reduction towards an approach that allows the ecological and social systems that surround a firm’s operations to thrive. This generally involves a firm seeking to reduce or eliminate its various negative impacts and to increase its positive impacts on environmental and social systems. An increasing number of firms are showing an interest in regenerative business approaches. However, more research is needed to understand how firms can move toward regeneration and how they resolve challenges and tensions that arise in the process.
PhD project description:	We are seeking a talented and motivated doctoral researcher with a solid understanding of sustainable business, biodiversity and other sustainability issues, and socio-ecological systems. The candidate we are looking for will conduct research at the intersection of business and socio-ecological systems, using systemic perspectives in their studies. The doctoral project aims at furthering theoretical and practical understanding of regenerative business. The main objective of this doctoral project is to shed light on how actors resolve challenges and tensions that may arise as firms pursue regenerative business approaches. The doctoral researcher will use qualitative and/or other suitable research methods to study the phenomenon of interest. Possible data sources include interview, survey, observational (field) data, and archival materials. The doctoral researcher will be based at the subject of Management and Organization/Turku School of Economics, but the interdisciplinary Biodiversity and Regenerative Business Research Group also involves researchers from the Biodiversity Unit/Faculty of Science. The doctoral project has interconnections with existing research projects funded by the Academy of Finland and the Research Council of Finland, which focus on biodiversity and systemic transformation (BIODIFORM) and Biodiversity Respectful Leadership (BIODIFUL). (See https://sites.utu.fi/biodiform/ and https://biodiful.fi/en/).
Specific requirements:	The position requires a proactive approach, motivation and diligence, interaction and team work skills, and a passion to learn new methods and perspectives. We expect a Master’s degree in management/organization, business, economics, or a closely-related field. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) solid understanding of sustainable business and sustainability issues (e.g., biodiversity) (2) interest and experience in conducting research on sustainability/regeneration at the intersection of business and socio-ecological systems, (3) experience of and interest in conducting high-quality research, using suitable (e.g., qualitative) methods.
Secondment:	Ivey Business School, Western University, Canada
Dept./Faculty to which the thesis belongs	Department of Management and Entrepreneurship/Turku School of Economics (TSE)
Principal supervisor / Project web page	Asst. Prof. Anne Quarshie, UTU/TSE, amquar@utu.fi https://sites.utu.fi/biodiform/ and https://biodiful.fi/en/

PhD project description:	We are seeking a doctoral researcher with a solid understanding of biodiversity loss and other global environmental issues, and socio-ecological systems. The candidate we are looking for will conduct research at the intersection of biodiversity and business and use systemic perspectives in conducting doctoral research. The field of expertise sought is in the remit of transformations toward biodiversity-respectful future. The doctoral researcher operates especially at the interdisciplinary crossroads of biodiversity and business research – two so far distinct disciplines that have begun to discover not only the need but also the various possibilities of closer collaboration. This raises questions as regards e.g. understanding biodiversity and biodiversity loss from a broad perspective and finding solutions for tackling biodiversity loss in the interface of different disciplines. While the position is particularly positioned at the crossroads between the disciplines of biodiversity and business studies research, in the remit of the research consortia SRC BIODIFUL (www.biodiful.fi ) and AoF Profi6 BIODIFORM, it is also connected to e.g. environmental sciences, future studies, food sciences and tourism research, with opportunities for conceptual integration between the disciplines. The doctoral researcher is located at the Biodiversity Unit of the University of Turku, Faculty of Sciences, , but the interdisciplinary Biodiversity and Regenerative Business Research Group also involves researchers from the Department of Management and Organization, Turku School of Economics. The position requires a proactive approach, motivation to do research in a multidisciplinary environment, motivation to seek and use new systemic approaches to study the theme beyond the traditional nature-culture divide, excellent interaction and team work skills, and a passion to learn new methods and perspectives. The selection process therefore also emphasizes the applicant’s experiences in teamwork and collaboration with different disciplines. The successful applicant will join an interdisciplinary team working at the crossroads of biodiversity, business studies and beyond and will be mentored during the research by a diverse set of senior researchers.
Specific requirements:	The applicant would benefit from having a good knowledge and understanding of global environmental issues, especially on biodiversity and biodiversity loss. We expect a Master’s degree in biodiversity research, environmental sciences, sustainable business, or other related or suitable fields.
Secondment:	Information coming soon
Dept./Faculty to which the thesis belongs	Biodiversity Unit
Principal supervisor / Project web page	Prof. Ilari Sääksjärvi, ileesa@utu.fi https://sites.utu.fi/biodiform/ and https://biodiful.fi/en/

Background:	The digital revolution is changing how climate risk data is collected, processed and turned into actionable climate adaptation solutions. Increased availability of satellite imagery over the past decade enables monitoring of climate change impacts over time and across regions. AI enables data to be rapidly processed and analysed. The internet, mobile phones and low-cost data collection technologies have potential to unlock local knowledge and combine it with Earth Observation (EO) -derived information. However, many climate services in Africa have not obtained the desired outcomes, as they have overlooked local needs and are too strongly relying on scientific, expert-driven data and knowledge, which have failed to operate in local decision-making systems. Co-creation of socially innovative and responsible climate risk data products is urgently needed based on synergistic use of mass data, advanced analytics, information and communication technologies, and concepts of open and shared knowledge for local action.
PhD project description:	We are seeking a talented doctoral researcher with good knowledge of geospatial data, digital technologies (incl. GIS, EO, ML/AI) and citizen science methodologies adaptable to the context of global South cities, particularly Africa. The PhD project aims at contributing to improved management of climate related risks particularly in African cities with actionable data and localized digital solutions. The main objective of the project is to develop integrated and socially innovative digital data and methods, which use opportunities of digital revolution (FAIR data, incl. Copernicus and other Earth observation (EO) data, open-source technologies, artificial intelligence and automation), in combination with bottom-up community engagement and citizen science approaches for improved mapping and management of climate risks in Sub-Saharan African cities. The doctoral researcher will carry out scientific research together in a multi-disciplinary research group. PhD researcher will be conducted in selected African cities and requires close collaboration with multiple stakeholders operating in the cities as well as national and global stakeholders to ensure scalability and transfer of developed data and methodologies. The doctoral project is linked to the Tanzania Resilience Academy cooperation with several Tanzanian Universities, land use planning practitioners, the GFDRR/World Bank and the German Aerospace Centre (DLR).
Specific requirements:	The position requires an active approach, diligence and cooperation skills, willingness to work as a part of a team and a passion to develop impact-driven new methodologies and tools. We also expect a well-completed Master’s degree in disciplines, such as Geography, Geospatial sciences, Geoinformatics, Data Science, Engineering, Urban planning or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) strong geospatial data exploration, analysis, processing, modelling and visualization skills, b) knowledge and understanding of African cities as complex multi-stakeholder decision-making systems, and (3) interest and motivation to operate between science and practice and learn how to co-create operative, automated and scalable digital climate risk data products and/or tools.
Secondment:	World Bank/ Global Facility for Disaster Reduction and Recovery (GFDRR), German Aerospace Center (DLR) ) – German Remote Sensing Data Center (DFD).
Dept./Faculty to which the thesis belongs	Department of Geography and Geology / Faculty of Science
Principal supervisor / Project web page	Prof. Niina Käyhkö, Department of Geography and Geology / Faculty of Science, nivuore@utu.fi Digital Data Innovation Hub, Tanzania Resilience Academy (https://resilienceacademy.ac.tz) and UTU Tanzania Team (https://tanzania.utu.fi/).

Background:	Climate risks are complex and vulnerability is multidimensional in African cities, which lack baseline knowledge, digital data, tools and skills to make informed decisions. At the same time, cities are the future of African prosperity with their in-migration, young and increasingly educated population, improved digital infrastructures, and new job opportunities enabled by emerging digital economies. Accelerating and scaling digital and green transition and climate resilience in African cities requires a strategy that localises digital solutions, connects local actors to global digital goods, platforms and partnerships and builds from the talent and engagement of the new generation of African youths. Engaging youth for digital public works opportunities and digital data collection campaigns related to climate adaptation solutions is much needed. There is also a need to develop innovative youth and especially female engagement and skills-building methods, which complement existing formal modes of learning and provide youths with actionable digital climate resilience skills, competences and opportunities for employment.
PhD project description:	We are seeking a talented doctoral researcher with a good knowledge of open data, open-source tools, digital technologies, youth-led initiatives and public works in Africa, and skills in using mixed methods approaches, which combine quantitative and qualitative methods in a living-lab type of innovation setups. The main objective of the project is to diversify the ways youths (particularly female youths) can be introduced to and engaged into different digital public works and novel data collection campaigns related to the co-creation of green transition and climate resilience solutions in African cities using opportunities of digital revolution (FAIR data), open-source technologies and participatory methodologies. The PhD project aims at contributing to digital and green transition and their sustainability and local ownership particularly in African cities with improved engagement of local youths to public works with complementary learning and employment benefits. A special focus will be given to female empowerment, addressing inequalities and challenges, which females may face. The project will also pay specific attention to co-designing engagement modalities that successfully match ‘demands’ from public organisations and industry with the ‘supply’ (youth skills growth, future employment opportunities). The doctoral researcher will carry out the research in the Digital Data Innovation Hub of the University of Turku and the doctoral project is linked to the Resilience Academy cooperation with several Tanzanian Universities, the GFDRR/World Bank and the German Aerospace Centre (DLR). Pairing youths with mentors from academia, industry and international development circles will be part of the research environment of this project. The research will be conducted in selected African cities and requires close collaboration with multiple stakeholders operating in the cities as well as national and global stakeholders to ensure scalability and transfer of developed youth and community engagement methodologies.
Specific requirements:	The position requires proactive approach, diligence and skills of working in multi-cultural team using living lab, community-based and participatory place-based approaches and a passion to develop novel and impact-based youth engagement methods and approaches. We expect a successfully completed Master’s degree in disciplines such as Geography, Community development, Spatial planning, Urban resilience, Geospatial sciences, or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) strong experience on community or youth engagement and open data related research and practice b) knowledge and understanding of cities as complex socio-ecological systems, and (3) interest and motivation to operate between science and practice and learn how to co-create novel youth engagement methods and incentives for public works initiatives and practices in African cities.
Secondment:	World Bank/ Global Facility for Disaster Reduction and Recovery (GFDRR), German Aerospace Center (DLR) – German Remote Sensing Data Center (DFD).
Dept./Faculty to which the thesis belongs	Department of Geography and Geology / Faculty of Science
Principal supervisor / Project web page	Prof. Niina Käyhkö, Department of Geography and Geology / Faculty of Science, nivuore@utu.fi Digital Data Innovation Hub, Tanzania Resilience Academy (https://resilienceacademy.ac.tz), UTU Tanzania Team (https://tanzania.utu.fi/) and Sustainable Landscape Systems Research Group (https://sites.utu.fi/landscape/)

Background:	Antibiotic resistance (AMR) is one the most pressing global health problems. Recent work on synthetic microbial communities suggests that the evolution of antimicrobial resistance is dependent on surrounding microbial community. For example, some resistant species can protect susceptible species by detoxifying the growth environment through hydrolysis of antimicrobials, while other species can constrain the evolution of resistance through competition for space and nutrients. However, most of this evidence come from simple lab experiments, and as a result, very little is known about the ecology and evolution of antibiotic resistance in more complex communities, especially in natural environments.
PhD project description:	Keywords: AMR in microbiomes, synthetic communities, experimental evolution, microbial ecology, phages Our research aims to understand the evolution of antimicrobial resistance in multi-trophic communities containing bacteria and/or parasitic phages. Ecology and evolution of AMR can be studied using already characterized synthetic bacterial communities or certain focal species. Several experimental systems are available in Hiltunen and Friman labs (second supervisor, Ville Friman, U Helsinki https://villefrimanscience.weebly.com), including laboratory and soil microcosms, and tomato plant rhizosphere mesocosm. Soil and plant rhizosphere are of special interest since they are potentially overlooked hotspots for AMR where bacteria commonly engage in chemical warfare with each other, using antimicrobial compounds as weapons to compete for space and nutrients. Unaddressed questions include how bacterial competition and lytic phages affect the ecological dynamics of these systems, having potential evolutionary feedback on selection for AMR. Moreover, we are interested in how phage resistance correlates with AMR, and whether these evolutionary processes are magnified in the plant rhizosphere relative to the soil. This information is important for understanding the antibiotic resistance problem in One Health perspective and potential risks associated with the transfer of antibiotic resistance genes through food production systems. Moreover, understanding AMR in communities is fundamental for predicting antibiotic resistance evolution in human and animal associated microbiomes. The proposed project can focus on studying AMR in synthetic microbial communities using one or several experimental systems available in supervisors’ labs (please see our publication lists for recent work).
Specific requirements:	We are seeking to work with a highly motivated PhD researcher with background in microbiology, microbial evolution and/or ecology, bioinformatics or genetics.
Secondment:	Secondment University of Helsinki, Finland (Prof Ville Friman https://villefrimanscience.weebly.com)
Dept./Faculty to which the thesis belongs	Biology / Faculty of Science
Principal supervisor / Project web page	Prof. Teppo Hiltunen, teppo.hiltunen@utu.fi https://www.expevo.org/

Background:	Anthropogenic climate change increases the incidence of natural disasters such as heatwaves, flooding, droughts, and consistent environmental degradations, and facilitates range shifts of species across latitudes and altitudes. Invading species may enrich biota in the new environment, but accumulating evidence also suggests associated risks. For example, non-native species may outcompete native species and facilitate the spread of novel pests and pathogens in agriculture. Thus, climate change may cause threats to food security, and associated political and social conflicts. In recent years, there has been growing evidence about the potential use of microorganisms (including bacteria and fungi) to protect plants. Plant beneficial bacteria has been utilized to protect plants against pests, pathogens and hostile environments (e.g. Mediterranean area suffering from increasing droughts). However, the molecular mechanisms involved are yet unclear, as well as the consequences of its use in a changing climate.
PhD project description:	In this project, we utilize computational biology techniques to identify the molecular mechanisms involved in plant-microbe interactions that may facilitate the emergence of novel pathogen or plant-beneficial microbe strains in a changing climate. Among others we will tackle the following questions: What are the molecular mechanisms involved in the evolution of plant beneficial microbes? How wide-spread are these mechanisms in bacteria? How does the environment modulate these plant-microbe interactions? What are the potential effects in a changing climate? The project will utilize data from public repositories, as well as plant-associated microbes collected in other ongoing projects.
Specific requirements:	The candidate will be someone with a biology, biotechnology or biochemistry background, and highly motivated to utilize computational biology techniques to address a global problem. Ideally, with a Master in bioinformatics (or equivalent), and proficient in data analysis (linux, shell, python, R, etc.) and English language. Experience in a microbiology lab will be highly valued.
Secondment:	Eurecat, Technology Center of Catalonia
Dept./Faculty to which the thesis belongs	Biodiversity Unit
Principal supervisor	Prof. Kari Saikkonen, karisaik@utu.fi

Background:	Invasive alien species are a main driver of biodiversity loss and, thus, a global challenge for ecosystems, science and conservation. Marine invasions typically inflict fundamental changes in the native communities and these may cascade down to producer abundance and species composition, which may potentially alter ecosystem functions such as biomass accumulation, carbon sequestration and transfer of matter, processes that have become particularly important with the climate change.
PhD project description:	Here we focus on the ecosystem effects of an ongoing invasion in the Baltic Sea, using the current population increase and dispersal of the mud crab (Rhithropanopeus harrisii) in shallow littoral habitats as our model system. We will comprehensively analyse the ecological feedbacks of the invasion on community composition of invertebrates and macroalgae, and their consequent effects on ecosystem function. Our approach provides novel scientific knowledge on ecosystem effects of invasions, valuable for marine conservation decisions and for management of species invasions. Furthermore, our approach adds knowledge on the contribution of shallow littoral habitats and their biotic communities on the Baltic Sea ecosystem function. As a legacy of long history of anthropogenic eutrophication on the Baltic Sea, there is considerable self-sustaining internal nutrient load hampering attempts to improve ecosystem status through nutrient load reductions. The extended amount of shallow rocky littoral habitat is a special characteristic of the Archipelago Sea (Finnish west coast), which at the same time is a eutrophication hot spot due to agricultural nutrient runoff. We know very little about the role of these shallow areas on nutrient and carbon assimilation and flows. The baseline data on these processes produced here contributes to our understanding about the internal nutrient load from shallow habitats, which is critically important for evaluation of effectiveness of alternative conservation measures to improve the ecological status of Archipelago Sea. The project will be carried out in collaboration with the Finnish Environment Institute that has expertise on monitoring and modelling under-water biodiversity.
Specific requirements:	The ideal candidate is expected to have a MSc degree in ecology, evolutionary or marine biology, environmental sciences or other related field, and is talented, creative, highly motivated and shows enthusiasm for science. A successful candidate would benefit from having practical experience in experimental research, underwater field work and maritime boating, and good command of statistical analysis and merits in scientific writing.
Secondment:	Finnish Environment Institute (Syke) and / or Åbo Akademi University
Dept./Faculty to which the thesis belongs	Department of Biology
Principal supervisor	Prof. Veijo Jormalainen, veijor@utu.fi

Background:	The green transition in EU entails rapid expansion of renewable energy sources such as windpower and solar energy. In Finland, construction of wind turbines is currently at an unprecedented rate. In addition, medium to large solar energy sites (covering 10s to 100s of ha) are being constructed. While renewable energy is a key part of the green transition, it also creates a conflict with wildlife as construction of these sites may constitute mortality and habitat loss over relatively large areas around the facilities. Land-based renewable energy is in Finland typically constructed in forests. While there is substantial research on effects of wind power on wildlife in coastal areas, we know relatively little about its effects in forests.
PhD project description:	We are looking for a doctoral researcher with good knowledge on wildlife ecology, conservation biology and sustainable energy production. The PhD project aims to provide insights into how the sustainability of renewable energy with respect to wildlife can be increased and is of relevance to the industry. A main objective of the project is to study how different vulnerable wildlife species are affected by the construction of renewable energy facilities. This will be done by using mainly existing movement and occurrence data on selected wildlife species inhabiting areas close to power plants, but there is potential to also collect new data. The focus is mainly in vertebrate species such as eagles, owls, wolves and wild forest reindeer, but the detailed plan is modified according to the interests of the doctoral researcher.
Specific requirements:	The candidate is expected to have a MSc degree in Ecology, Evolutionary biology, Wildlife science, Zoology, Applied biology, Forest sciences, Environmental Sciences.
Secondment:	Natural Resources Institute Finland (Luke)
Dept./Faculty to which the thesis belongs	Department of Biology / Faculty of Science
Principal supervisor / Project web pages	Prof. Toni Laaksonen, tokrla@utu.fi https://animalecology.utu.fi/ https://www.researchgate.net/lab/Brommer-Lab-Jon-E-Brommer https://www.luke.fi/en/projects/tuuliriista

Background:	Biological invasions, which result from introductions of alien species, are identified as one of the major threats to biomes according to the UN Environment Programme (UNEP). They are causing ecological and economic problems across the world, including yield losses, displacement of resident species, and disruption of species interactions. For example, in the Nordic countries the total costs of invasive alien species are billions in USD and they are likely underestimated, with damage costs overweighing management costs. Humans introduce alien species intentionally or accidentally and may facilitate their spread. Human behaviour, beliefs, and lack of knowledge can also hinder management programmes, particularly if invasive species are considered charismatic or aesthetic. As an example, a study conducted in Scotland revealed that public support for eradication programmes varied depending on age, gender, and the level of previous knowledge of the respondents on invasive species. Ultimately, the efficient management of invasive species requires considering public perceptions in research and decision-making. To date, research on the socioeconomic factors affecting the perceptions of invasive species is scarce, with the majority of research (>90%) focusing on ecological impacts. Psychological well-being generally increases with increasing biodiversity. Given the rapid speed of urbanization around the world, urban public greenspaces will provide an important nature contact for many people in the future. However, urban environments harbour numerous alien species that benefit from the longer growing season of cities compared to those of rural areas. In Central European cities up to 40% of vascular plant species are non-native, which might lead to a conflict between the management of invasive species and recreational values of public greenspaces.
PhD project description:	In this project, we will investigate public awareness and the public perceptions of invasive alien species (IAS) focusing on socioeconomic factors that may influence these perceptions (e.g., age, education, outdoor activity, stakeholder group). Study questions can include (but are not limited to) the following: 1) Which socioeconomic factors determine the public perceptions of invasive species? 2) How do the public perceptions of invasive species change along an urban-rural gradient? 3) How are public awareness and perceptions related to the efficiency of invasive species management? The project will utilise data collected from online questionnaires and literature, and its scope can be narrowed down to certain taxonomic groups or ecosystems depending on the research interests of a doctoral researcher. The project will be carried out in collaboration with the Natural Resources Institute Finland – the research organisation that is involved in the national inventory of invasive species
Specific requirements:	The doctoral candidate should have a MSc degree in ecology, environmental sciences or a comparable field and motivation to learn quantitative skills (e.g., R, meta-analysis). The candidate would benefit from also having good organisational and data management skills, as well as excellent skills in written and oral English. Prior knowledge of invasive alien species in Northern Europe is a plus.
Secondment:	Natural Resources Institute Finland (Luke)
Dept./Faculty to which the thesis belongs	Department of Biology / Faculty of Science
Principal supervisor / Project web page	Dr. Satu Ramula, satu.ramula@utu.fi https://sites.utu.fi/popdyn

Background:	Autonomous aerial robotic solutions are set to play an essential role in climate change mitigation and enable long-term sustainability and efficient services across civilian and industrial applications. Unmanned aerial vehicles (UAVs) are already an important asset for environmental monitoring and sensing in remote environments and the creation of high-fidelity digital twins. In this project, the research activities delve into the underlying technologies in Robotics and AI that will investigate what levels of perception are required for an aerial robot to undertake autonomous missions in complex and remote environments.
PhD project description:	The research aims to enable efficient surface-aerial collaborative perception. The primary objective is to design and develop a heterogeneous surface-aerial system capable of advancing perception and autonomous monitoring in fluvial and coastal environments. This will involve leveraging a collaborative unmanned surface vehicle (USV) and a multi-UAV system to achieve long-term autonomy and comprehensive situational awareness, with sensors scanning from both the water surface and the air. The central focus lies in the design, development, and implementation of algorithms for collaborative autonomy, to explore distributed and centralized techniques for coordinating a fleet of UAVs and USVs in potentially unknown remote environments. The key goal is to ensure the effectiveness of these algorithms in real-world scenarios.
Specific requirements:	What we expect from the candidate is independence, collaboration and analytical skills. Motivation to work in a multinational and interdisciplinary team on multi-robot systems, embedded AI, and edge computing. We also expect a Master’s degree in fields, such as computer science, embedded systems, information technology, mechanical engineering or another relevant field. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) Python and C++ programming, (2) ML technologies, (3) deploying ML in resource-constrained devices, and (4) practical hands-on experience with (mobile) robots. In addition, we expect researchers to jointly carry out interdisciplinary research across different fields and leverage the opportunities for collaboration.
Secondment:	The University of Manchester
Dept./Faculty to which the thesis belongs	Department of Computing, Faculty of Technology
Principal supervisor / Project web page	Prof. Tomi Westerlund, tovewe@utu.fi tiers.utu.fi

Background:	Autonomous aerial robotic solutions are set to play an essential role in climate change mitigation and enable long-term sustainability and efficient services across civilian and industrial applications. UAVs are already an important asset for environmental monitoring and sensing in remote environments and the creation of high-fidelity digital twins. The research activities delve into the underlying technologies in Robotics and AI that will unlock efficient autonomous surface and aerial contact manipulation required for an aerial or surface robot to undertake autonomous missions in complex and remote environments.
PhD project description:	In this project, the aim is to investigate and optimize the control of this complex multi-robot system. A multi-modal perception framework for large-scale UAV mapping under uncertain conditions will be developed, including wind, snow, and changing environmental conditions, in fluvial and coastal environments. The goal is to optimize data collection through research on robot navigation and path/motion planning algorithms, ultimately creating a drone fleet-assisted environmental data collection system for the generation of high-fidelity digital twins. The emphasis is on ensuring that the developed algorithms can be effectively deployed in real-world scenarios.
Specific requirements:	What we expect from the ideal candidate is independence, collaboration and analytical skills. Motivation to work in a multinational and interdisciplinary team on multi-robot systems, embedded AI, and edge computing. We also expect a Master’s degree in fields, such as computer science, embedded systems, information technology, mechanical engineering or another relevant field. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) Python and C++ programming, (2) ML technologies, (3) deploying ML in resource-constrained devices, and (4) practical hands-on experience with (mobile) robots. In addition, we expect researchers to jointly carry out interdisciplinary research across different fields and leverage the opportunities for collaboration.
Secondment:	Hamburg University of Technology, Germany
Dept./Faculty to which the thesis belongs	Department of Mechanical and Materials Engineering, Faculty of Technology
Principal supervisor / Project web page	Assoc. Prof. Wallace Moreira Bessa, wallace.moreirabessa@utu.fi https://sites.utu.fi/smartsystems/

Background:	Past epidemics and environmental challenges, such as famines, have posed a long lasting pressure of natural selection on human genomes. The (genetic) structure of the human host community and its contact networks have affected pathogen exposure, and therefore the consequences on the human genomes. Genes related to immune response and metabolic pathways are among the key targets of selection under environmental pressures. Pleiotropic effects may produce co-occurrence with other traits, such as elevated risk for later life disorders (e.g Alzheimers). Finally, epigenomes may have been modulated with effects reaching beyond generations.
PhD project description:	In this project, we combine ancient and modern human DNA, pathogen genomics and life history trait data in Finnish context to examine the effects of past events on human genomes in the past versus present population. The project combines ancient genomic data covering the last 2,000 years with large modern genomic data collections. Moreover, archaeologically excavated soft tissue remains of individuals from the past four centuries may be analysed for exposures, to ascertain pathogen presence, and ultimately, to unravel the specific reasons for epidemic events taking place in the observed time and place. The information collected over the course of this study can be employed to estimate future risk factors for local and rapidly expanding epidemics, and to prevent the development of similar hotspots like those recognized from the historical time. This fully funded PhD project will be jointly supervised by Professor Päivi Onkamo and Title of Docent in Population Genetics Elina Salmela within the multidisciplinary Human Diversity consortium (https://sites.utu.fi/humandiversity/) and belongs to the UTU-GreDiT Doctoral Programme: Solutions for Green and Digital Transition and One Health perspective at the University of Turku. The position includes a 4-6 months secondment at the Max Planck Institute for Evolutionary Anthropology (MPI-EVA) Leipzig, Germany, that offers a strong quantitative base for research combining ancient DNA sequencing, population genomics, and historical epidemiology (https://www.eva.mpg.de/archaeogenetics/index/).
Specific requirements:	The PhD candidate should have a multidisciplinary background and Masters degree in population genetics, bioinformatics, evolutionary biology/medicine, microbial evolution or related fields. A successful candidate is a team player, has experience and interest to work with people and datasets from multiple disciplines, passion to learn new, strong quantitative skills in statistical genetics, and proficient English in writing and communication.
Secondment:	Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
Dept./Faculty to which the thesis belongs	Department of Biology, Faculty of Sciences.
Principal supervisor / Project web page	Prof. Päivi Onkamo, paivi.onkamo@utu.fi https://sites.utu.fi/humandiversity/

Background:	Human health stems partly from adaptations to diverse ancestral environments and the challenges posed by our rapidly changing modern world. Infectious diseases, in particular, have exerted significant selection pressures on human evolution, but the epidemics often affected some regions more than others. Also access to nature and microbes (e.g. forest cover, animal husbandry), resources (food scarcity, house type) and population structure (city/urban) vary through time and place and can fuel adaptations (e.g. immune responses) that enhance health in these environments. However, the impact of spatial disparities in disease outbreaks and environmental factors on both historical and current human health, including different disease susceptibilities (e.g. cardio-vascular diseases, cancers, cognitive disorders, auto-immune diseases), remains unknown.
PhD project description:	We are seeking for an enthusiastic and motivated PhD student with knowledge in evolutionary biology and health research, to investigate past and present variation in death causes in Finland. This PhD project draws upon extensive, multi-generational and multidisciplinary data from historical and modern Finland. The PhD project employs two distinct approaches: one focused on assessing regional disparities through time and the other on exploring family lineage-specific variation in death causes across generations in different environments. Together, these approaches offer valuable insights into the evolutionary origin of human health, shedding light on how our past environments have left their mark on our current disease susceptibilities. The PhD researcher will carry out research within the multidisciplinary Human Diversity consortium (https://sites.utu.fi/humandiversity/ ) and utilizes unique datasets from Finland: 1) the Human life history data. This is a multi-generational demographic dataset (e.g. all births, marriages, migrations, deaths) following the same family lineages from preindustrial to modern Finland (individuals born 1730-2022), 2) Cause-specific mortality data of entire Finland 1750-1850 and in contemporary day and 3) Cultural and environmental data, which includes ~100 cultural and environmental explanatory variables from each municipality in Finland. During the PhD project a 4-6 months secondment in the PandemiX Centre offers a strong quantitative base for research combining mathematical modelling, historical epidemiology, bioinformatics and clinical research (https://ruc.dk/en/research-centre/pandemix-center). The PhD researcher undertakes the following studies in the PhD thesis: 1) spatial variation in death causes across time 2) lineage-specific variation in death causes and 3) the variation caused by temporal, environmental and cultural characteristics or past epidemics.
Specific requirements:	The PhD candidate should have a multidisciplinary background and Masters degree in evolutionary ecology, evolutionary medicine/health/disease, health geography, anthropology or related fields. A successful candidate is a team player, has experience and interest to work with people and datasets from multiple disciplines, passion to learn new, strong quantitative skills in statistics, and proficient English in writing and communication.
Secondment:	PandemiX Centre, University of Roskilde, Denmark
Dept./Faculty to which the thesis belongs	Department of Biology/ Faculty of Science
Principal supervisor / Project web page	Dr. Mirkka Lahdenperä, mirkka.lahdenpera@utu.fi https://sites.utu.fi/humandiversity/

Background:	Many real life problems encountered in sustainable development are complex and difficult to model by conventional mathematical methods. Machine learning provides a wide variety of methods and tools for solving such problems by learning mathematical models from data. The predictions made by a learned model are based on a vector of feature values describing the input to the model. However, predictions do not come for free in real world, since the feature values of the input have to be bought, measured or produced before the model can be used.
PhD project description:	In this project, the aim is to develop machine learning algorithms that infer predictive models under an acquisition budget for expensive features. The budget can be determined in terms of the cost of feature extraction in prediction time, or in terms of the cost of feature extractors (e.g. physical sensors needed for prediction) or simultaneously both. Practical examples of the costs for which we have already developed solutions are the number of expensive or inconvenient operations needed for making a medical diagnosis for a patient and expensive chemical instruments needed for analyzing the quality of drinking water, et cetera. It has been shown that greedy optimization techniques are powerful tools for training cost sensitive machine learning models, but even better strategies can be developed for complicated structured budgets.
Specific requirements:	The position requires an active approach, diligence and cooperation skills, willingness to work as a part of a team and a passion to learn new. We also expect a Master’s degree in, for example, computer science, information technology, mathematics or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) Strong understanding on machine learning mathematics behind it (2) Good programming skills and good knowledge on python programming language.
Secondment:	Natural Resource Institute, Finland
Dept./Faculty to which the thesis belongs	Department of Computing / Faculty of technology
Principal supervisor	Prof. Tapio Pahikkala, aatapa@utu.fi

Background:	Advancements in machine learning (ML) have opened new avenues for improving natural resource inventory and biodiversity estimation due their potential to process vast and diverse datasets common in natural resource studies. This includes data from remote sensing, sensors, and other sources such as field samples. Althought ML has already significantly transformed the fields of natural resource inventory and biodiversity estimation, new methods are needed for handling aggregated data from multiple sources and understanding high-dimensional data heterogeneity. Additionally, there is a need for improved model performance assessment and uncertainty estimation in spatially correlated data.
PhD project description:	We are seeking a talented doctoral researcher with good knowledge on machine learning (deep learning), remote sensing and use of spatiotemporal datasets. The PhD project aims at advancing the state-of-the-art in ML-driven natural resource inventory and biodiversity estimation. Main objective of the project is to develop new ML methodologies with a particular focus on deep learning approaches to fuse data from multiple sources at different spatiotemporal resolutions and to understand the heterogeneity and commonality of high dimensional and large sample size data to find relevant and coherent information among multiple data subpopulations. The doctoral researcher will conduct scientific research in collaboration with the multi-disciplinary Algorithms and Computational Intelligence (ACI) research group. The focus of the PhD thesis will encompass the following ML method developments: 1) Early, middle, and late data fusion; 2) Addressing imbalanced training sets and optimizing the selection of field sampling sites 3) Assessing input importance and estimating model output uncertainty; 4; Evaluating model complexity and performance, particularly in the context of spatially autocorrelated data related to natural resource inventory and biodiversity estimation.
Specific requirements:	The position requires an active approach, diligence and cooperation skills, willingness to work as a part of a team and a passion to learn new. We also expect a Master’s degree in, for example, computer science, information technology, mathematics or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) Strong understanding on machine learning and especially deep learning and mathematics behind them (2) Good programming skills and good knowledge on python programming language; (3) Experience in computational modelling and spatio-statistical approaches; (4) Experience in remote sensing and GIS softwares is advantage.
Secondment:	University of Parma, Italy
Dept./Faculty to which the thesis belongs	Department of Computing / Faculty of Technology
Principal supervisor	Prof. Jukka Heikkonen, jukhei@utu.fi

Background:	Mineral deposits contain critical raw materials (CRM) and battery minerals that demand is increasing globally. At the EU level, securing the supply of CRM´s are essential for the more self-sustained green digital future. Paleoproterozoic Svecofennian crust in Finland and Sweden contains several hydrothermal and orthomagmatic mineral deposits that are suitable sources for vast range of metals important for green transition, such as Co and Ni, and other base metals that are essential components of today’s rapidly growing battery technologies.
PhD project description:	We are seeking a talented doctoral researcher with good knowledge on ore geology including hydrothermal and orthomagmatic processes, and stable and radiogenic isotopic systems. The PhD project aims to progress green transition by studying CRM potential mineral deposits with state-of-the-art analytical methodologies. Main objective of the project is to better understand the source, processes, energy drivers and trapping mechanisms involved in the formation of so-called “battery mineral deposits”. The doctoral researcher will carry out scientific research together with the multi-disciplinary research group of the Luleå university of technology. PhD researcher will focus on the Fennoscandian geology cross the border to have broadly the same temporal evolution at regional scale. The PhD thesis will focus: 1) understanding the geological controls on the formation of these deposits and the variability in major and trace element distributions and mineral compositions; 2) fluid/magmatic activity with the U-Pb method, and use S, Fe, Cu and potentially non-traditional isotope systems to find out origin and mobility of the metals; 3) better harmonizing the geological understanding across the borders to better understand the truly orogenic-scale metallogenetic controls in the Fennoscandian shield. This requires a comprehensive approach taking to account the form of the deposit, the intensity of mineralization, mineral compositions of several deposits which have broadly the same temporal evolution at the truly regional scale.
Specific requirements:	The position requires an active approach, diligence and cooperation skills, willingness to work as a part of a team and a passion to learn new. We also expect a Master’s degree in, for example, ore geology, Precambrian geology, bedrock geology, or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) Knowledge and interest on ore geology; (2) Strong understanding of ore forming processes; (3) Good geochemistry method understanding; (4) Interest and experience in outdoors & field work.
Secondment:	Luleå university of technology
Dept./Faculty to which the thesis belongs	Department of Geography and Geology/ Faculty of Science
Principal supervisor	Prof. Esa Heilimo, esa.heilimo@utu.fi

Background:	The Earth’s Early felsic crust is known to be formed by melting of mafic rocks, but the origin of these rocks is unclear. Within a 2.7-billion-year-old Archean terrain in the Lake Inari area, northern Finland, we have identified metabasalts showing elevated Cu, Ni, Co, and Cr concentrations that might be indicative of hydrothermal activity in the bottom of an ancient ocean.
PhD project description:	We are seeking a talented doctoral researcher with good knowledge on geochemistry including isotope geology, magmatic petrology and geochemical modelling. The PhD project aims to contribute to the information needed by today’s rapidly growing green energy technologies – from wind turbines and electricity networks to electric vehicles –by using state-of-the-art elemental and isotopic research and instrumentations. The main objective of the project is to define the source and tectonic setting of the metabasalts and their role in the formation of Archean felsic crust and, in terms of green energy, evaluating the critical green energy element potential of Archean basalts in general. Basalts are mafic igneous rocks crystallized from mantle-derived Mg and Fe rich magmas extruded at or very near the surface of the Earth. They contain varying amounts of critical elements such as copper, nickel, cobalt, chromium, gold, and platinum group elements. The doctoral student will contribute to the resolving of the source of the felsic crust and estimating the critical green energy element potential of Archean basalts by studying the following topics: 1) the major and trace element distributions, 2) Sr-Nd-Pb isotope systematics, 182W isotopes, and 87Sr/86Sr ratios of apatite to find out their origin, and 3) U-Pb and Lu-Hf geochronology of. A Special emphasis is put on the S, Cu, Ni, Co, Cr and Au-PGE studies to detect possible signs of ore-forming fluid activity. The doctoral researcher will collect field data on artic area and apply the state-of-the-art in-situ measurement techniques, build geochemical, elemental, and isotopic models of the Archean crust formation.
Specific requirements:	The position requires an active approach, diligence and cooperation skills, willingness to work as a part of a team and a passion to learn new.  We also expect a Master’s degree in, for example, petrology, Precambrian geology, isotope geology, or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) knowledge and interest on isotope geology; (2) good skills in magmatic and metamorphic petrology; (3) interest and experience in geochemical modelling; (4) interest and experience in outdoors & field work.
Secondment:	LUOMUS/University of Helsinki, Finland
Dept./Faculty to which the thesis belongs	Department of Geography and Geology/ Faculty of Science
Principal supervisor	Prof. Esa Heilimo, esa.heilimo@utu.fi

Background:	Glacial geomorphologies of formerly glaciated landscapes can offer further insight into properties of past ice sheets, their thermal regimes and velocity, as well as complex hydrological systems driving glacial dynamics. The hydrological systems operating on past and present ice sheets have been recognized as significant research topics due to their influence on ice sheet dynamics and, ultimately, the global sea level rise. The subglacial hydrological system has remained as a relatively poorly known component in ice sheet behavior, although a number of advances have been made towards its better understanding in recent years. The basal hydrological system is typically conceptualised as existing in either (i) an inefficient, distributed state in which water is transmitted through thin films, linked-cavities, or as Darcian flow through a porous sediment, or (ii) an efficient, channelised system in which water is routed through Nye channels eroded down into the underlying substrate (N-Channels) or Röthlisberger channels (R-Channels) and Hooke channels (H-Channels) formed within the ice itself. Temporal and spatial transitions between inefficient and efficient modes of drainage (murtoo forming environment) has important implications for drainage and ice sheet dynamics during deglaciation and in a rapidly warming climate.
PhD project description:	By using high-resolution LiDAR digital elevation models, combined with maps of Quaternary deposits and morpho-lithogenetic units, mapped subglacial meltwater corridors and ice-lobe dynamic features of the Fennoscandian Ice Sheet (FIS), it is pursued to identify, map and classify meltwater drainage routes around the former FIS. The use of machine learning and pattern recognition techniques in detecting variations and configuration of subglacial hydrological systems is preferred. Studies can be supplemented with fieldwork, ground geophysics and trench excavations, jointly with existing research team currently working with murtoo and meltwater route sedimentology in the FIS area. The aims of the project are to (i) identify typical characteristics of meltwater routes in different glacial dynamic regions (ice lobes) and cold-based areas around the FIS, (ii) understand the role of bedrock litho- and techtonostratigraphy on the distribution of meltwater routes, (iii) work out the role of localized meltwater inputs, fan-shaped hollows and blister marks along the meltwater routes, (iv) identify spatial and temporal changes of hydrological systems operating on the surface, inside and at the base of the ice sheets during FIS deglaciation. Ultimately, the goal is to increase understanding on how previous ice sheets underwent deglaciation under different dynamic settings (warm- and cold-based) so that it allows to better predict how our modern ice sheets will continue to respond to ongoing climate change. For research group and recent activities, see https://sites.utu.fi/reward/
Specific requirements:	The position requires a Master’s degree in, for example, Quaternary geology, hydrology or glacial hydrology, physics, or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (i) knowledge and understanding on glacial dynamics, glacial hydrology and sedimentation processes, (ii) experience with remote sensing and geographic information systems (GIS), (iii) experience in computational modelling is highly beneficiary.
Secondment:	Oulu Mining School/University of Oulu
Dept./Faculty to which the thesis belongs	Department of Geography and Geology/ Faculty of Science
Principal supervisor / Project web page	Prof. Antti E.K. Ojala, antti.e.ojala@utu.fi https://sites.utu.fi/reward

Background:	Ammonia serves as a crucial energy vector and plays a significant role in agriculture as fertilizer. Traditionally, the production of ammonia relies on the energy-intensive Haber-Bosch process. The necessity for new sustainable technologies to generate eco-friendly NH3 is evident. In the PhotoMicrobes group, we specialize in the development of photosynthetic production systems, harnessing the potential of cyanobacteria and microalgae as efficient biocatalysts. The capability of some cyanobacteria to perform N2-fixation presents a promising green strategy for the production of ammonia. This approach is distinguished by its carbon-neutrality, energy efficiency, and potential for sustainability.
PhD project description:	We are seeking a talented doctoral researcher with a good knowledge on bioengineering, biotechnology and cell metabolism. The PhD researcher will join the truly international PhotoMicrobes research group (http://www.utu.fi/photo-microbes) and will have access to all the state-of-the-art equipment and methods available in the PhotoSYN infrastructure. The central objective of this research is to establish a solar-driven photosynthetic platform using N2-fixing filamentous cyanobacteria for ammonia production. The project will involve the investigation of electron transport in heterocysts, specialized N2-fixing cells, the engineering of cyanobacterial strains for efficient NH3 production, and the development of a proof-of-concept photobioreactor system incorporating living materials with immobilized cells. The integration with H2 production technologies using low-cost materials will be carried out together with Prof. Pekka Peijo’s group.
Specific requirements:	The position requires a Master’s degree in, for example, cell physiology, microbial biology and biotechnology or related fields. Prior experience with photosynthetic organisms is considered a benefit.
Secondment:	Information is coming soon.
Dept./Faculty to which the thesis belongs	Department of Life Technologies/Faculty of Technology
Principal supervisor / Project web page	Prof. Yagut Allahverdiyeva-Rinne, allahve@utu.fi http://www.utu.fi/photo-microbes

Background:	Hydrogen (H2) is an energy carrier that holds great promise globally as a solution for addressing climate challenges. Currently, there are three approaches for producing green H2 from abundant sunlight and water: 1) PV systems connected to water electrolysis, 2) integrated systems for direct solar-to-H2 conversion, and 3) direct photobiological H2 production. Green algae are excellent examples capable of producing H2 through the direct photobiological approach by splitting water with energy from sunlight. Unfortunately, the process is difficult to sustain due to the high sensitivity of H2 production to O2 co-evolved in photosynthesis and its competition with other metabolic pathways for photosynthetic reductants. Recently, we devised a breakthrough pulse-illumination protocol that allows redirecting photosynthesis towards H2 production and significantly enhancing H2 production yields.
PhD project description:	We are seeking a talented doctoral researcher with a good knowledge of bioengineering, biotechnology and cell metabolism. The PhD researcher will join the truly international PhotoMicrobes research group (http://www.utu.fi/photo-microbes) and will have access to all the state-of-the-art equipment and methods available in the PhotoSYN infrastructure. The central objective is to investigate the mechanisms of H2 photoproduction in algae under pulse-illumination protocol, engineer algal cells to perform the steady-state water biophotolysis and transfer the engineered cells to the solid-state biodegradable (nano)matrices, thus creating the true biocatalysts for efficient H2 production. The work will also involve the modelling of CO2 capturing, light distribution and water exchange within the volume to engineer the most efficient biocatalytic architecture. This aspect of the research will be conducted in collaboration with Dr. Guillaume Cogne (Nantes, France).
Specific requirements:	The position requires a Master’s degree in, for example, biotechnology, cell physiology, microbial biology or related fields. Prior experience with photosynthetic organisms is considered a benefit.
Secondment:	University of Nantes, France
Dept./Faculty to which the thesis belongs	Department of Life Technologies/Faculty of Technology
Principal supervisor / Project web page	Prof. Yagut Allahverdiyeva-Rinne, allahve@utu.fi http://www.utu.fi/photo-microbes

Background:	Climate change and the growing global population demand urgent solutions for the development of climate-resilient and highly productive crops. Photosynthesis utilizes light energy to convert CO2 into carbohydrates, fuelling crop growth. Balanced photosynthesis under environmental stress is crucial for both survival and agricultural advancement. Enhancing photosynthesis in plants is a complex task that necessitates the consideration of multi-level regulatory mechanisms while addressing source-sink relationships. Barley (Hordeum vulgare) is the third most important cereal crop in Northern and Central Europe. Several European laboratories and projects are currently dedicated to the genetic improvement of barley for increased crop yield. Importantly, the results of these scientific investigations can be translated to other important crop species (e.g. Triticeae).
PhD project description:	We are searching for a skilled doctoral researcher with a background in molecular biology, genetic engineering, and plant science. The primary objective of the project is to modify barley to improve photosynthesis under challenging environmental conditions. Multiple approaches will be employed to address bottlenecks in photosynthetic light reactions and optimize source-sink capacity, thereby enhancing crop productivity. The PhD researcher will receive training in the operation of various cutting-edge equipment and methodologies for photosynthesis research available at the PHOTOSYN infrastructure of the University of Turku. During a secondment in the group of Prof. Ivo Frebort (CATRIN, Olomouc, Czech), the PhD researcher will utilize advanced CRISPR/Cas9 genome editing technologies in barley. The engineered crops will undergo assessment in field experiments conducted by the company.
Specific requirements:	We expect a Master’s degree in fields such as plant science, molecular biology, biotechnology, or related disciplines. Previous experience in photosynthesis would be advantageous.
Secondment:	CATRI (the Czech Advanced Technology and Research Institute), Palacky University Olomouc, Czech Republic
Dept./Faculty to which the thesis belongs	Department of Life Technologies/Faculty of Technology
Principal supervisor / Project web page	Prof. Yagut Allahverdiyeva-Rinne, allahve@utu.fi http://www.utu.fi/photo-microbes

Background:	Climate change is making traditional farming impossible in many regions of the world. In addition, Covid-19 and the war in Ukraine have highlighted the importance of local food production independent of the international transport of resources. Indoor farming secures local food production independent of weather conditions. However, indoor farming is energy-intensive and requires major leaps in energy efficiency to be ecologically and economically sustainable large scale food production method. The recent development of indoor farming sector has been built on available generic LED technologies, while scientific photosynthesis knowledge on plant light energy requirements and use have not been utilised. In optimal conditions we must be able to control the light spectrum and intensity based on the capacity of the photosynthetic machinery. The technology development has been limited by the lack of research equipment to measure the efficiency of electricity-light-biomass conversion; especially the capacity of the photosynthetic machinery to use light energy for CO2 fixation. The task is not trivial and requires the control over multiple overlapping parameters which is not possible without elaborate system for data processing and feedback. We have now developed such a research platform, Minibiosphere, which enables AI-driven optimization of growth conditions for maximal production with minimal energy. Optimisation based on the light use efficiency of plants is the only foreseeable way to significantly improve the energy efficiency of indoor farming. Besides plants, the project involves engineered cyanobacteria, photosynthetic microbes which are being developed as next-generation biotechnology host for the light-driven production of desired chemicals from CO2, and photobioreactor productions systems that serve here as a test setup for evaluating the designed optimization methods.
PhD project description:	The aim of the project is to identify the boundary conditions within which technological advancements are poised to enhance efficiency—a pivotal step in delineating the potential role of indoor farming in future food systems. By leveraging optimization techniques alongside adaptive control, machine learning, and data analytics, this endeavor is poised to revolutionize indoor farming, paving the way for a sustainable and resilient agricultural future system where energy efficiency is taken into account in indoor farming.
Specific requirements:	The position requires an active approach, diligence and cooperation skills, willingness to work as a part of a team combining photosynthesis research, biotechnology, IoT and AI research. We also expect a Master’s degree in, for example, information technology, computer science, control theory or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) knowledge of control theory, adaptive control and machine learning based data analytics; (2) Experience in adaptive control and machine learning, experience in programming languages related to computer science and control theory (e.g. Python, Matlab), knowledge of IoT devices and embedded systems (3) Interest in plant-machine interaction and basic understanding from bioenergetics is advantage.
Secondment:	Iontau Ltd, Finland
Dept./Faculty to which the thesis belongs	Department of Computing / Faculty of Technology
Principal supervisor / Project web page	Prof. Jukka Heikkonen, jukhei@utu.fi www.utu.fi/plant-machine-interactions

Background:	Climate change is making traditional farming impossible in many regions of the world. In addition, Covid-19 and the war in Ukraine have highlighted the importance of local food production independent of the international transport of resources. Indoor farming secures local food production independent of weather conditions. However, indoor farming is energy-intensive and requires major leaps in energy efficiency to be ecologically and economically sustainable large scale food production method. The recent development of indoor farming sector has been built on available generic LED technologies, while scientific photosynthesis knowledge on plant light energy requirements and use have not been utilised. In optimal conditions we must be able to control the light spectrum and intensity based on the capacity of the photosynthetic machinery. The technology development has been limited by the lack of research equipment to measure the efficiency of electricity-light-biomass conversion; especially the capacity of the photosynthetic machinery to use light energy for CO2 fixation. The task is not trivial and requires the control over multiple overlapping parameters which is not possible without elaborate system for data processing and feedback. We have now developed such a research platform, Minibiosphere, which enables AI-driven optimization of growth conditions for maximal production with minimal energy. At molecular level the system can be used for investigating how the structure and function of the photosynthetic machinery affects the plant’s light use under different conditions and, on this basis, to design photosynthetic machinery for improved performance. In parallel, the platform can be used for evaluating engineered cyanobacterial strains producing specific target chemicals, and to study molecular-level determinants behind the conditional effects.
PhD project description:	The overall aim of the project is to maximise the energy efficiency of indoor agriculture, and future biotechnological applications that base on the use of photosynthetic production hosts, as well as to study the potential of genetically engineered plants designed for controlled environments. In this context, the specific goals of the PhD project include determining the light use efficiencies of different plant and cyanobacterial mutants and investigating the molecular mechanisms affecting the efficiency in different light and environmental conditions.
Specific requirements:	The position requires an active approach, diligence and cooperation skills, willingness to work as a part of a team combining photosynthesis research, biotechnology, IoT and AI reserch. We also expect a Master’s degree in, for example, molecular plant biology, biochemistry, biotechnology, or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) Knowledge and interest on photosynthesis; (2) Strong understanding on bioenergetics; (3) Interest and experience on technical devises; (4) Understanding the logic of programming.
Secondment:	Iontau Ltd
Dept./Faculty to which the thesis belongs	Department of Life Technologies/ Faculty of Technology
Principal supervisor / Project web page	Assistant professor Mikko Tikkanen, misati@utu.fi www.utu.fi/plant-machine-interactions

Background:	Current hydrogen electrolysis technologies are designed to operate 8000 hours per year, to be able to reach reasonable cost of hydrogen production during the lifetime of the units. They also rely on expensive catalyst materials such as Pt and Ir, require fluorinated polymers, or require difficult start/stop procedures. However, hydrogen and chemicals are estimated to be the cost effective approach for long duration storage. Therefore, methods to flexibly produce hydrogen with low capital cost are required to utilize low cost electricity when plenty of wind and solar power is available.
PhD project description:	We are seeking a talented doctoral researcher with good knowledge of electrochemistry and interest in electrocatalysis. The PhD project aims to enable flexible green transition by developing more flexible hydrogen production technologies relying on low cost materials but performing at lower efficiency. The project will investigate the trade-off between reduced capital cost, higher flexibility and reduced efficiency. The doctoral researcher will carry out scientific research within the materials engineering unit at University of Turku, with a secondment in Technical University of Munich, Germany. They will undertake the following studies in the PhD thesis: 1) testing of activity and stability of low costs materials for hydrogen production and 2) perform the technoeconomic assessment of the developed technologies; 3) design of electrochemical systems for hydrogen production. The doctoral researcher will collect data on electrocatalytic activity and stability by applying the state-of-the-art in-situ measurement techniques, process the data, perform technoeconomic assessment and design alternative systems.
Specific requirements:	The position requires an active approach, diligence and cooperation skills, willingness to work as a part of a team and a passion to learn new. We also expect a Master’s degree in, for example, physical chemistry, materials engineering, chemistry, physics, or related fields. Due to the nature of the described PhD project, the candidate would benefit also from having e.g. the following skills: (1) Experience in laboratory work; (2) Knowledge or interest in electrochemistry; (3) Experience or interest in materials characterization; (4) Experience or interest in technoeconomic analysis.
Secondment:	Technical University of Munich, Germany
Dept./Faculty to which the thesis belongs	Materials Engineering / Faculty of Technology
Principal supervisor	Prof. Pekka Peljo, pekka.peljo@utu.fi

PhD research projects

The UTU-GreDiT PhD projects

1) Remote sensing and morphodynamic modelling in hydromorphological and sediment connectivity analyses

2) Climatological and anthorpogenic controls on catchment scale hydrological processes in Boreal and Sub-Arctic environments

3) Nature-based solutions in urban water management and climate change mitigation

4) Pollution-related food chain changes and their consequences to passerine birds

5) Ecophysiological consequences of surface water browning on aquatic fauna

6) Diverse values of nature supporting human and other species wellbeing in urban green infrastructure planning

7) Challenges and tensions in regenerative business preventing green and just transition

8) Effects of regenerative business on species and ecosystems

9) Big Earth data, citizen science and AI in co-creation and deployment of innovative climate risk data products and tools for African cities

10) Open data, digital tools and youth engagement in public works for green transition and climate resilience in Africa

11) Understanding the ecology and evolution of antibiotic resistance in microbiomes

12) Plant-microbe interactions in changing climate

13) Ecosystem consequences of an invasive marine predator in shallow benthic habitats

14) Effects of renewable energy sources on wildlife in the boreal forest

15) Understanding the public perceptions of invasive species to enhance management

16) Collaborative Unmanned Surface and Aerial Vehicles for Sustainable Environment Monitoring

17) Drone Fleet-based Active Environmental Data Perception in Uncertain and Dynamic Environments

18) Human genomic changes due to past epidemics and environment in north-eastern Europe

19) Evolution of human health in past and modern environments

20) Cost sensitive machine learning for sustainable development

21) New ML methods for natural resource inventory and biodiversity estimation

22) The battery and base metal mineralization processes and comparison of Svecofennian metallogenic provinces

23) The origin and green energy element potential of Archean metabasalts

24) Morphogenetic evidence of subglacial hydrology underneath the Fennoscandian Ice Sheet – implications to rate of ice sheet melting, evolution of drainage systems and glacial dynamics

25) Engineering the photosynthetic biohybrid system for solar-driven NH3 production

26) Engineering solid-state algal cell factories for efficient H2 production

27) Enhancing Photosynthesis to boost Crop Yield and Climate Resilience

28) Photosynthesis research and AI-based energy optimization of controlled environment agriculture

29) Molecular light acclimation mechanisms affecting the light-use efficiency of photosynthetic machinery in controlled environment agriculture

30) Flexible hydrogen electrolysis

PhD research projects

The UTU-GreDiT PhD projects

1) Remote sensing and morphodynamic modelling in hydromorphological and sediment connectivity analyses

2) Climatological and anthorpogenic controls on catchment scale hydrological processes in Boreal and Sub-Arctic environments

3) Nature-based solutions in urban water management and climate change mitigation

4) Pollution-related food chain changes and their consequences to passerine birds

5) Ecophysiological consequences of surface water browning on aquatic fauna

6) Diverse values of nature supporting human and other species wellbeing in urban green infrastructure planning

7) Challenges and tensions in regenerative business preventing green and just transition

8) Effects of regenerative business on species and ecosystems

9) Big Earth data, citizen science and AI in co-creation and deployment of innovative climate risk data products and tools for African cities

10) Open data, digital tools and youth engagement in public works for green transition and climate resilience in Africa

11) Understanding the ecology and evolution of antibiotic resistance in microbiomes

12) Plant-microbe interactions in changing climate

13) Ecosystem consequences of an invasive marine predator in shallow benthic habitats

14) Effects of renewable energy sources on wildlife in the boreal forest

15) Understanding the public perceptions of invasive species to enhance management

16) Collaborative Unmanned Surface and Aerial Vehicles for Sustainable Environment Monitoring

17) Drone Fleet-based Active Environmental Data Perception in Uncertain and Dynamic Environments

18) Human genomic changes due to past epidemics and environment in north-eastern Europe

19) Evolution of human health in past and modern environments

20) Cost sensitive machine learning for sustainable development

21) New ML methods for natural resource inventory and biodiversity estimation

22) The battery and base metal mineralization processes and comparison of Svecofennian metallogenic provinces

23) The origin and green energy element potential of Archean metabasalts

24) Morphogenetic evidence of subglacial hydrology underneath the Fennoscandian Ice Sheet – implications to rate of ice sheet melting, evolution of drainage systems and glacial dynamics

25) Engineering the photosynthetic biohybrid system for solar-driven NH3 production

26) Engineering solid-state algal cell factories for efficient H2 production

27) Enhancing Photosynthesis to boost Crop Yield and Climate Resilience

28) Photosynthesis research and AI-based energy optimization of controlled environment agriculture

29) Molecular light acclimation mechanisms affecting the light-use efficiency of photosynthetic machinery in controlled environment agriculture

30) Flexible hydrogen electrolysis

30) Flexible hydrogen electrolysis