55 parallel-computing-numerical-methods Postdoctoral positions at Technical University of Denmark in Denmark
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Energy our research is targeting exactly this, and we are looking for a postdoc to numerically aid our team in the design of biomagnetometers. It is possible to get a deeper understanding of how the brain
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reaction evolution mechanisms for magnesium-based binders, leveraging state-of-the-art experimentation and numerical modelling tools. This position is part of the prestigious Villum Synergy project
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meet security, compliance, and integration requirements. You will collaborate with various professionals and act as the link between technical teams, clinical teams, and project management. In parallel
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commercial activities. The PhD position is based in the Section for Bioinformatics, which focuses on developing and applying computational methods to solve complex problems in genomics, systems biology, and
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will develop imaging-driven quantitative Mass Spectrometry-based omics methods, both at bulk population and single-cell levels, for this project. You will work closely with experts in cellular signalling
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invites applications for a postdoctoral position within a dynamic research team dedicated to understanding and improving taxation behavior through behavioral and experimental methods. This is a unique
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implementation of these within optimized computer code, but also large-scale applications of the resulting methods to various chemical problems of interest. Candidates with a strong background in theoretical and
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to computational tools like RFdiffusion, ProteinMPNN, or AlphaFold. Experience with mammalian cell culture in two and/or three dimension Ability to perform biochemical and imaging methods Strong analytical skills
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(e.g., based on physiological signals or direct inputs from occupants) and developing algorithms, including machine learning methods. The work will include statistical modelling, data-driven modelling
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: Background in Data Science, Computer Science or related fields; Working experience in implementing AI models (not just loading pre-trained model). PyTorch framework is preferred; Experience with APIs