198 computer-programmer-"https:"-"U"-"UCL" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" positions at Technical University of Munich
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University of São Paulo, Brazil. This position focuses on developing advanced computer vision methods and hardware setup for detecting and predicting plant diseases in soybean cultivation. About Us The Chair
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of distributed computing, machine learning, image and text analysis, randomized data structures, high-performance computing, and quantum algorithms. Beyond this research, we aim to support computational thinking
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, dynamics, and interactions in complex environments and live mammalian cells. By combining ultra-high-field NMR with complementary biochemical, computational, and cellular approaches, the project will
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. • Computational efficiency: Designing adaptive and physics-aware strategies (e.g., optimized residual selection, physics-based zooming) for real-time inference. • Practical usability: Developing robust, user
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activities. ________________________________________ Candidate Requirements ✅ PhD degree in Engineering, Computer Science, Systems & Control, Statistics, Computational Physics, Computational Chemistry
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experimental and computational research in the areas of novel aviation and maritime propulsion (combustor design, thermo-acoustics, SAF, H2, ammonia) as well as hydrogen mixtures and refrigerant safety
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Systems Control Theory Formal Methods Reachability Analysis Computational Geometry Context The applicant will be directly advised by Prof. Matthias Althoff (https://www.ce.cit.tum.de/cps/members/prof-dr-ing
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Universitätsklinikum rechts der Isar der TU München Ismaninger Str. 22, 81675 München http://kornlab.med.tum.de The position is suitable for disabled persons. Disabled applicants will be given preference in case
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into real-world applications in Geriatronics. Your Profile PhD in Robotics, Mechanical Engineering, Electrical Engineering, Computer Engineering, Mechatronics, or a closely related field. Proven experience in
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dynamic team. As part of the newly funded ERC Synergy consortium EPIC, you will develop scalable and robust software to train and apply AI models for regulatory genomics. About us The Chair of Computational