193 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at Technical University of Munich in Germany
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-cell communication, and cellular plasticity—all without destroying the sample. (https://www.cell.com/cell/fulltext/S0092-8674(25)00288-0 , https://www.biorxiv.org/content/10.1101/2024.11.11.622832v1
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command of written and spoken English • Experience with qualitative research methods is an asset • Good knowledge of machine learning /data mining in science • Good programming skills in at least one
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using AI to solve the world’s most pressing challenges? Do you believe that technology should serve a higher purpose? The Civic Machines Lab at the Technical University of Munich (TUM) is looking for a
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interaction-rich scenarios. Ideal applicants will have a strong M.Sc. in machine learning, control, or safety, and hands-on experience with robotics. Apply now: https://lnkd.in/dNjmv835. Deadline: ASAP. We
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. MATLAB, C/C++, Python. Highly motivated and keen on working in an international and interdisciplinary team. Applicants with strong background in the following fields are preferred: Machine Learning Formal
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where wildly creative ideas for a hopeful future can emerge, and will provide an inspiring learning environment to students. The position is funded by and affiliated with TransforM – the Munich Center
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civil and military operations“ and „operational analysis and evaluation“. The combination of these research focus areas provides an ideal platform for interdisciplinary research in simulation and
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in machine learning and an interest in agentic AI, deep reinforcement learning, and applications in economics. The full-time positions (100%) are initially offered for two years, with the possibility
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office.ethics@mh.tum.de https://get.med.tum.de/ www.tum.de If you apply in writing, we request that you submit only copies of official documents, as we cannot return your materials after completion
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electrification strategy, the research aims to develop a multidisciplinary framework that combines microstructure modeling, machine learning, and probabilistic simulation to link manufacturing parameters, foam