40 condition-monitoring-machine-learning Postdoctoral positions at Technical University of Munich
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06.12.2021, Wissenschaftliches Personal The professorship of Data Science in Earth Observation is seeking six new PhD candidates/PostDocs for its new center for Machine Learning in Earth Observation
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Researchers: Ph.D. in Computer Science or Mathematics, ideally with a background in one or more of the following areas: Optimization, Game Theory, Machine Learning Applicants must demonstrate: • An excellent
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fields. Strong programming skills in Python, Java, C++, etc. A solid foundation in generative AI, machine learning, and related areas. Interest in Speech/Language Processing and its application. Know-how
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following areas: Mathematical Analysis/ Numerical Analysis/ Theoretical Machine Learning Please note: Applications from candidates with degrees in other disciplines (e.g., Computer Science, Engineering) will
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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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collisions and maximize efficiency through innovative AI-based movement and maneuver planning. For the first time, innovative machine learning concepts, such as “shadow learning”, are being used. Appropriate
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machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization methods, machine learning algorithms, and
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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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on the design and evaluation of innovative data- and machine learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop new optimization
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with R, statistical and spatial analysis Excellent communication and teamwork skills Excellent organizational skills Experience with field work in post-disturbance forest conditions (desired) Experience