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relevant fields of biology (e.g., systems, evolutionary, developmental, computational), physics, mathematics or related fields. In the appointment process, special attention will be given to research skills
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) Computer Science/Mathematics/Physics and at the second cycle level, 60 credits in Life Science, Computer Science Mathematics, Physics or Bioinformatics including a 30 credit Degree Project (thesis). Selection
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Are you passionate about applying computational approaches to solve problems in biomedicine? We are now looking for an Industrial PhD student in Data-Driven Life Sciences to work on a cutting-edge
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this unique program Duties At the Physics Department of Gothenburg University we are announcing the position as DDLS PhD student in Data driven cell and molecular biology. Data driven cell and molecular
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, engineering physics, biomedicine, or similar Documented skills in data-driven analysis (machine learning using python with TensorFlow, PyTorch, or similar) and computational statistics Specific knowledge of big
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life science (DDLS) uses data, computational methods and artificial intelligence to study biological systems and processes at all levels, from molecular structures and cellular processes to human health
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, probability theory, etc) A competence in quantitative topics equivalent to a mathematics, statistics, physics, computer science, or engineering degree is required (if your degree was not in one of these domains
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, computer simulations and various statistical approaches to increase understanding of the ecological and evolutionary processes that underlie speciation and ecological diversification in the context
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Sintorn, Professor in digital image processing, at the Department of Information Technology and conducted alongside researchers developing computational methods with a particular focus on deep learning and
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a research projects that link regulatory variation to molecular, cellular and organismal phenotypes using a systems genetics approach. This fully computational position focuses on integration of human