172 parallel-computing-numerical-methods "Simons Foundation" Postdoctoral positions in Denmark
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to protein engineering and molecular cloning, Experienced in bioinformatic genome analysis and computational tools related to protein structure analysis and prediction, Sufficient expertise in standard
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The project may address national or international problems, and should do so using appropriate methods, qualitative and/or quantitative. Access to Danish data sources, such as registry data, respondents
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. Join us at the Department of Electrical and Computer Engineering, Aarhus University, where we are developing semantic-aware communication that leverage edge AI, semantic reasoning, and efficient time
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use your skills to answer fundamental biological questions in health and disease. The successful candidate is expected to leverage their skills in proteomics and computational analysis to interrogate
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Postdoc in development and testing of electrodes for liquid alkaline water electrolysis - DTU Energy
electrochemical testing by means of various voltametric methods and electrochemical impedance spectroscopy. As a formal qualification, you must hold a PhD degree (or equivalent). We offer DTU is a leading technical
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in ion transport and (2) using machine learning methods to design protein binders. The incoming postdoc will have the opportunity to mould the project to a significant degree. The candidate should have
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). The successful candidate will contribute to the Nudge2Green research project, applying software development and AI methods to design digital nudging tools that promote sustainable consumer behavior in food choices
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. Over the last decade HLA class II antigen presentation has been accurately described and methods developed that predict this event with a high level of confidence. In comparison, a detailed understanding
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(XAI) methods to improve the understanding of key drivers controlling peatland conditions and ecosystem functioning. The research project will primarily focus on implementing and merging analyses
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(XAI) methods to improve the understanding of key drivers controlling peatland conditions and ecosystem functioning. The research project will primarily focus on implementing and merging analyses