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We are looking for a highly motivated, skilled, and persistent PhD student with experience in computational fluid dynamics (CFD) and some knowledge in structural analysis. The research aims
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of the material and its properties. This research position focuses on computational approaches to assess the influence of the material microstructure on structural integrity, incorporated in technical models
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build the sustainable companies and societies of the future. The EISLAB division of the Department of Computer Science, Electrical and Space Engineering conducts research within Cyber-Physical Systems
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: • Designing and conducting multi-omics analyses (including genomics, transcriptomics, proteomics, metabolomics). • Constructing new AI-driven multi-omics models • Supporting occasional teaching and supervision
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for Sustainable Housing and buildings”, you will: Develop an ontology of regenerative building production by analyzing how regeneration affects on-site praxis, economic structures, and business models and
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year project, funded by the DDLS program, we aim to develop AI-based tools in design of affinity ligands, such as the prediction of binding interactions between proteins. Data-driven life science (DDLS
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advanced biostatistics/machine learning analyses, but also with other types of analysis. The work involves supporting Swedish researchers under a “user fee-based” support model. The projects will differ in
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computational simulation techniques are used. The research is applied to understand orthopaedic problems and to develop better methods to improve tissues regeneration. The group encompasses about 15 scientists
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Science, Natural Science and Geography. The teaching includes responsibility for a bachelor's programme, a master's programme, single subject courses, and courses in the Primary School Teacher Programme
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] Subject Areas: Theoretical Physics / Statistical physics Machine Learning Complex Systems Computational Science and Engineering / AI/ Machine Learning , Artificial Intelligence , Data Sciences , Machine