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willingness to learn: High-performance computing (distributed systems, profiling, performance optimization), Training large AI models (PyTorch/JAX/TensorFlow, parallelization, mixed precision), Data analysis
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, nationality, ethnicity, sexual identity, physical abilities, religion or age. Qualified applicants with physical disabilities will be given preference. Learn more about diversity at Helmholtz Munich Our
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Neurobiologie (ZMNH) Main tasks You will join the Institute of Medical Systems Biology and the bAIome Center for Biomedical AI (baiome.org) to complement our lively and enthusiastic team of machine learning and
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Postdoc Position (f/m/d) for any of the following topics: Combining non-equilibrium alchemistry with machine learning Free energy calculations for enzyme design Permeation and selectivity mechanisms in
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of quantitative data collection and analysis - Knowledge of French - Willingness to learn Phyton as a programming language - Knowledge of oral history of the Holocaust For further information, please contact Dr
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
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machine learning methods in the context of biological systems Experience with programming (e.g., Python, Perl, C++, R) Well-developed collaborative skills We offer: The successful candidates will be hosted
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group (https://bckrlab.org). We focus on high impact applications and work on knowledge-centric AI and biomedical machine learning including multi-omics integration, single cell analysis, and sequential
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 1 month ago
. Bert de Groot) is inviting applications for a PhD Student or Postdoc Position (f/m/d) for any of the following topics: Combining non-equilibrium alchemistry with machine learning Free energy calculations
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collisions and maximize efficiency through innovative AI-based movement and maneuver planning. For the first time, innovative machine learning concepts, such as “shadow learning”, are being used. Appropriate