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We are pleased to announce a postdoctoral position focusing on developing advanced computational techniques to reduce the complexity in simulating lake physical dynamics at scale. Borrowing from
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The Rantalainen group is focused on application of machine learning and AI for development and validation of predictive models for cancer precision medicine, with a particular focus computational pathology. Our
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to address critical computational challenges in simulating the physical dynamics of millions of lakes worldwide. The successful candidate will create innovative solutions that significantly enhance large-scale
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Karlstad University, Physics Position ID: Karlstad University -Physics -POSTDOC [#29463] Position Title: Position Location: Karlstad, Varmland, Sweden Subject Areas: Physics / Condensed Matter
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(Physics, Applied Physics, Nanotechnology, Computer Science, Engineering, or equivalent), obtained no more than three years prior to the application deadline (according to the current agreement with
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human development globally.” The Lab is mainly located at DSAI and IAS. The Swedish Research Council funds this Lab through a Research Environment Program and a Consolidator Grant. Pilot funding comes
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bioinformatics, physics, statistics, computer science, computational biology, or related fields. Experience programming in Python (or R) as well as bash/shell scripting. Experience with machine-learning and deep
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energy use and minimizing environmental impact. This collaborative effort brings together expertise in materials science, physics, polymer chemistry, and composite mechanics, with a particular emphasis on
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, research and teaching are conducted in computer science, computer engineering, and informatics. We have two expanding departments in these areas, with around 50 employees. Your placement will be in
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diseases, including genetics, epidemiology, immunology and epigenetics, with excellent clinical cohorts and experimental models. The Applied Immunology & Immunotherapy group is physically located