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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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in transition is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about
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in transition is key. We also take pride in delivering education to enable regions to expand quickly and sustainably. In fact, the future is made here. Are you interested in learning more? Read about
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managing large amounts of data by designing structured databases (PostgreSQL, MySQL). Machine learning methods such deep learning for analysis of proteomics data and classification of cancer profiles. Since
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evolutionary analysis. A central component of the research will be to develop machine learning and deep learning methods trained on coding sequences and protein structure to extract patterns in data and to draw
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. Qualifications Required: PhD. Applicants who have obtained a PhD degree or achieved the equivalent competence in seven years or less prior to the end of the application period will be given priority. Research
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Physics (with focus on machine learning and bone microscopy analysis, Soft Matter Lab) The Department of Physics at the University of Gothenburg is located in the center of Gothenburg, with approximately
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. The project explores the role of tumor-promoting inflammation in cancer progression through bioinformatics-driven, machine-learning and multi-omics analyses integrated with experimental data. Ideal candidates
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than 40 PhD students and postdocs. Research at the DSAI ranges from foundational methods in machine learning (e.g., optimization, bandits and reinforcement learning) to application domains in biophysics
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includes participating in research projects and third cycle courses. The work duties will also include teaching and other departmental duties (no more than 20%). Your research focus will be machine learning