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/ This postdoctoral fellow position is part of a new Career Programme for early-stage researchers in Educational Sciences initiated by the Umeå School of Education. The Career programme aims to strengthen Educational
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application! Work assignments Subject area: Computational studies of the influence of microstructural features on the structural integrity of metallic materials using machine learning Subject area description
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model design and analysis as well as statistical model parametrization and validation techniques. This Postdoc position is part of a five-year research program funded by the Wallenberg Foundation, aimed
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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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. The research group is part of the National Program for Data-driven Life Science (DDLS), generously funded by the Knut and Alice Wallenberg Foundation: www.scilifelab.se/data-driven/ Our group focuses on studying
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position is part of a five-year research program funded by the Wallenberg Foundation, which aims to develop and apply computational tools to understand the evolution of biodiversity (see https
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coast and in offshore areas. The position will also include further development of ongoing data analyses within the national data collection program (DCF), which plays a key role in improving our
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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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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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of gravitational wave physics and the LISA mission. Knowledge of python and other programming languages is a strong advantage. Experience of handling large data sets within international collaborations. It is