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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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curious and motivated postdoc with a PhD in biomedical engineering, physics, materials science, organic chemistry—or similar—and a drive to explore new frontiers in science. 👉 Learn more and apply here
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biological systems and processes at the molecular level. The focus is on experimental and theoretical studies of the physical properties of proteins in solution. We have state of the art facilities for protein
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The Royal Institute of Technology (KTH), Theoretical Physics Position ID: The Royal Institute of Technology (KTH) -Theoretical Physics -POSTDOC20253 [#29689] Position Title: Position Type
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leave, sick leave, or military service. Contract terms The position is a temporary full-time employment for two years with the possibility of a one-year extension. The position requires physical presence
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with technology facilities (national and international) and the clinic, as well as on genuine enthusiasm for the topic and methodology. Application process: The application must contain the following documents in
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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time, paid out on a six months basis. In exceptional cases, shorter periods may be acceptable. Application process An application must contain the following documents in English or Swedish: A complete
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for the scholarship period. Selection process The following documents (in pdf-format) must be submitted when applying for a scholarship Cover letter, max 1 page, describing your background, research interests and what
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, diversity and equal conditions is both a question of quality for KTH and a given part of our values. For information about processing of personal data in the recruitment process. It may be the case that a