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. Antonio Scialdone’s group at Helmholtz Munich, a leading European hub for AI in biology. The successful candidate will design and implement physics-informed machine learning frameworks and predictive models
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. Become a part of our team and join us on our journey of research and innovation! Be
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strong foundations in machine learning and artificial intelligence, as well as a solid mathematical background. The position requires a strong interest in exploring multiple research directions toward
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-Phenomenology (hep-ph) , High Energy Physics , High Energy Theory , Machine Learning , Neutrino physics , Particle , Particle Physics , Particle Theory , QCD , Theoretical high energy physics , Theoretical High
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23.02.2026 Application deadline : 30.04.2026 The Autonomous Systems Lab at the University of Tübingen is searching for a Postdoctoral Researcher in machine learning (m/f/d, E13 TV-L, 100%) limited
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Germany | 21 days ago
AI in biology. The successful candidate will design and implement physics-informed machine learning frameworks and predictive models to uncover how gene expression and mechanical forces interact
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it comes to running experiments an affinity to AI technology (incl. machine learning, computer vision) (German) permit to perform animal experiments (equivalent to FELASA B or C) desirable previous
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assessment, programming and machine learning. If so, we encourage you to apply! You will develop exposure and physical vulnerability maps for past and future (1970-2100) and integrate these into a flood risk
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 19 hours ago
for Demographic Research, Rostock This network focuses on “scientifically motivated engineering” to design, build, and test digital prototypes—such as machine learning models and large language models—that serve as
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Job description: DESY The CMS Quantum Computing group develops generative machine learning models for detector simulations, specifically the simulation of showers in calorimeters: Proof-of-principle