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of organic semiconductor materials. Work assignments This project, funded by the Wallenberg Academy Fellows programme https://kaw.wallenberg.org/en/research/creating-greener-semiconductors , aims to provide a
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analysis, Python programming, and deep learning frameworks (e.g., TensorFlow, PyTorch) is expected. Prior work in cancer research or medical imaging is an asset. The successful candidate will join an
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society. With unique research expertise, we offer education at the undergraduate and graduate levels, as well as within our international master's programs. The Electronics Materials and Systems Laboratory
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research area. Candidates must be fluent in spoken and written English and highly motivated. Candidates are expected to pursue and plan research independently, but also to function in a team. Excellent
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of the ProWater Project (The use of industrial by-products as secondary resources in wastewater treatment) funded by the EU Interreg Aurora programme with project partners from Northern Sweden and
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. Documented experience and interest in developing models coupling the dynamics of soil, plants, and the atmospheric boundary layer as well as strong quantitative and programming skills (in MatLab, R, Python, C
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into consideration. The applicant should have good knowledge of automatic control, optimal control, statistics, and optimization. Furthermore, good programming skills are required, including Python and C++, and
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dimensions of climate extremes. The proposal must include: Project title (max. 20 words) Abstract (max. 150 words) Research questions or hypotheses Relevance to LUCSUS–CLIMES key themes Research plan and
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degree in relevant fields (bioinformatics, immunology, computational biology, mathematics, and/or statistics). Strong programming skills in R and/or Python Demonstrated strong ability in analyzing high
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publications in relevant research area. Candidates must be fluent in spoken and written English and highly motivated. Candidates are expected to pursue and plan research independently, but also to function in a