39 high-performance-computing Postdoctoral positions at Technical University of Munich in Germany
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mission-driven researcher to join a high-impact joint project with the World Wide Fund For Nature (WWF). We are reimagining how the world’s largest mission driven organizations plan, execute, and measure
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the development of novel optical technologies addressing significant biological and medical challenges. The Mission: The successful candidate will play a key role in an ambitious research program focused
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(especially LLMs / VLMs) Human-AI Interaction Or Bring-your-Own research topic Who We Are Looking For: We seek highly motivated and talented individuals passionate about AI, Human-Computer Interaction, Eye
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learning, medical image computing, biomedical engineering, medical physics, or related field Strong Python and PyTorch experience Solid publication record and ability to communicate research results
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training machine learning models (ideally with a focus on LLM), high-performance computing, data management, and software architecture Strong Python programming skills and familiarity with machine learning
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(PhD, 75%, 30h per week). Remuneration is in accordance with the German public tariff scheme (TV-L), salary group E 13. The successful candidates will be part of the Munich Climate Center and the Earth
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, quantitative readouts, define performance metrics, and validate results experimentally, helping convert laboratory scale prototypes into a compact, portable system. Your Profile: The successful applicant must
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qualifications: • A completed Master’s degree (or equivalent) in a relevant discipline, such as philosophy, neuroscience, psychology, medicine, law, social sciences, computer science, or a related field • Strong
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. The postdoc position (m/f/x) is limited to 24 months but can be extended for another 24 months (extension is subject to a positive performance evaluation). About us… Founded in 2002, TUM School of Management is
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, reliability, and consistent behavior. Learning-based controllers can achieve high performance in complex and uncertain environments, yet ensuring predictable operation under distribution shifts, sensor noise