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-Holstein (UKSH), is seeking a PhD student with a strong background in statistics, machine learning (ML)/artificial intelligence (AI), or bioinformatics. Our group develops novel computational and statistical
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plate array microscope for simultaneous time-lapse video microscopy, enabling high-throughput single-cell analyses of rapidly migrating cells. You will be responsible for Developing new machine learning
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theoretical methods and algorithms are required. The research project aims at deriving priors for Bayesian methods from atomistic simulations and machine learning. It also offers the opportunity to work with
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compiler, code generation, computer architecture and machine learning would be beneficial an independent, target- and solution-driven work attitude inter- and multidisciplinary thinking an integrative and
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research environment for biophysics. Our group combines molecular dynamics simulations with machine learning techniques to understand how proteins, biomembranes, and small drug-like molecules interact
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tools like ViennaRNA and NUPACK) and MD simulations (e.g., with GROMACS). Strong skills in statistical data analysis and machine learning in Python and R are expected, along with experience working in
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research group “Machine Learning for Biomedical Data” led by Prof. Dominik Heider and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles of Reproduction. The CRC 1748 involves
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Postdoc (f/m/d) on Generative AI for de Novo Protein Design / Completed university studies (PhD) ...
for Advanced Systems Understanding (CASUS) is a German-Polish research center for data-intensive digital systems research. The Department of Machine Learning for Infection and Disease is looking for a Postdoc (f
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or machine learning, proficiency in deep learning techniques (CNN, VIT, diffusion, GAN) Good understanding of the mathematical foundations of machine learning Mastering python and related AI software
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Professor (W3 / W2 with Tenure Track to W3) for Materials and/or devices for Photonics and Quantum T
quantum technologies. This research can be complemented by digital methods of process simulation and optimization, as well as machine learning. Requirements include an outstanding PhD in materials science