50 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"U.S" positions at Technical University of Munich
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on advanced machine learning and emulation approaches. Key responsibilities: The candidates will be expected to work on the following tasks: - Develop machine learning (ML) methodologies appropriate
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related discipline. Strong expertise in medical imaging and/or machine learning. Excellent programming and research skills. Interest in translational research and interdisciplinary collaboration with
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12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5
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Bayesian machine learning to improve risk management for bridge portfolios. We offer a funded PhD position in an excellent research environment. The project Our infrastructure is aging, and decisions about
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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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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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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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Technologies at TUM’s School of Engineering and Design is looking for a doctoral researcher (f/m/d) in the area of Collaborative Machine Learning for the Energy Transition. You are passionate about machine
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Candidates (f/m/d) in Machine Learning Applications to Sustainable Energy Management. You are passionate about applying cutting-edge information technology to solve the energy and climate crisis and would like
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for safety-critical bilateral teleoperation. The research will leverage a combination of passivity-based control methods and machine learning techniques to enable reliable and robust teleoperation in uncertain