186 machine-learning "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" "UCL" positions at Technical University of Munich
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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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-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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on developing the imaging system as well as novel machine learning approaches for image analysis and disease classification using field data from German and Brazilian agricultural trials. Responsibilities Design
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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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. 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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involve the integration of: Advanced motion planning and control algorithms Multi-modal perception techniques (e.g., vision, tactile, force) Machine learning models for physical behavior prediction and
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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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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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electrification strategy, the research aims to develop a multidisciplinary framework that combines microstructure modeling, machine learning, and probabilistic simulation to link manufacturing parameters, foam
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management skills • Experience with qualitative or mixed-methods research • Familiarity with AI, machine learning, neurotechnology, or robotics research contexts • Interest in science policy, governance