50 parallel-computing-numerical-methods research jobs at Technical University of Munich in Germany
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advanced machine learning methods for multimodal and 3D medical image analysis in musculoskeletal medicine, in close collaboration with clinicians and computer scientists. PhD or Postdoctoral Researcher
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activities. ________________________________________ Candidate Requirements ✅ PhD degree in Engineering, Computer Science, Systems & Control, Statistics, Computational Physics, Computational Chemistry
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computer aided methods. Qualifications and Experience • Outstanding academic degree in materials science, metallurgy, metal physics or similar degree • Excellent doctorate with focus on computational
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of Orthopaedics and Sports Orthopaedics and the Institute for AI and Informatics in Medicine. We work at the intersection of artificial intelligence, medical imaging, and clinical practice, developing methods
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, investigates how children and adults actively seek, select, and evaluate information to learn about the world. The lab combines behavioral, computational, and cross-cultural approaches to study curiosity
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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
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, engineering, data science, and computer science. Skill Development: Our extensive qualification concept goes beyond research, offering targeted training in research methods, project management, and leadership
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, international political economy and European integration theories. Methodologically, it draws on a plurality of approaches, notably qualitative methods.
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hubs for STS, we are a lively intellectual community of 80+ researchers from numerous disciplines and fields of specialization. As a department, we deliver 2 Master’s programs and design STS content
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the possibility of an extension. TASKS: Mathematical modeling and development of inverse methods (e.g. Bayesian inversion, optimization based methods, sparsity promoting methods based on L1-norm minimization and