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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 1 month ago
analysis, image analysis, statistical, and machine learning methods, choosing the approach that best fits the scientific question. Investigate systematically what information is contained in imaging data
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BAM Bundesanstalt für Materialforschung und -prüfung | Berlin, Berlin | Germany | about 2 months ago
on the Scaled Boundary Finite Element Method (SBFEM) – for modelling the propagation of guided ultrasonic waves in pipelines The task includes the refinement of existing SBFEM implementations and their extension
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Heidelberg Institute for Theoretical Studies (HITS gGmbH) | Heidelberg, Baden W rttemberg | Germany | about 8 hours ago
) in Geometric Deep Learning to join the Machine Learning and Artificial Intelligence (MLI) g roup to perform research in geometric deep learning for materials science. This research is part of
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) to learn about modelling, resilience and RD metrics, starting at M21 The successful candidate will join an interdisciplinary cohort of doctoral researchers and benefit from ReDiLEEP training in response
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Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. | Dortmund, Nordrhein Westfalen | Germany | 3 months ago
Developing computational framework for 3D shape modeling towards biological insights Developing AI-based representation learning framework for data-driven cell modeling Report findings and methods in
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computer simulations Working in close collaboration with theoretical physicists to test models and develop new insights Your Profile Bachelor's degree in physics Master’s degree/diploma in condensed matter
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looking for a PhD candidate to work on research at the intersection of machine learning, data privacy, and medical imaging. The position is part of a three-year research project that investigates how
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, and related fields (e.g., Graph Machine Learning) Tasks: scientific research in at least one of the above-mentioned research areas collaboration in national and international research projects, possibly
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sustainable operation of future energy networks by combining our knowledge of energy systems with cutting-edge developments in machine learning, generative AI, and digital infrastructures. Your Job
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Learning at TUM works on machine learning, artificial intelligence, and information processing, with a current focus on foundation models, data-centric research, and applications to scientific and medical