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conducted in close collaboration with Everllence (formally known as MAN Energy Solutions). The developed methods have to be tested in simulation and on real engines. Previous Work https://openreview.net/pdf
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Profile: A Master`s degree and an excellent PhD degree in Biochemistry, Chemistry, or a related Molecular Science Proven Track Record in Machine Learning, Molecular Simulations, Chemoinformatics
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to the Technical University of Munich (TUM), deals with the multifaceted interactions between politics, society, business and technology in research, teaching and practice. It was established by the Bavarian State
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qualifications: PhD or equivalent achievement (proof of independent research capability) in Machine Learning, Computer Science, Physics, Mathematics, or a related field Deep theoretical knowledge and extensive
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approaches are gaining importance for autonomous vehicles. However, the training and certification of autonomous systems with machine learning components is a huge challenge, since the learned behavior is
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-scale research facilities (e.g. DESY, ESRF), including coordination and setup of experiments Development of data workflows and analysis strategies (in collaboration with our machine learning team
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-XRF, Raman, FTIR in reflection mode) to enable multimodal data fusion and automated material characterization. • Apply and further develop machine-learning and statistical models (e.g. PCA, SAM
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funded German research initiative. Project Description: Carbon black is an indispensable component of numerous everyday products – from car tires and seals to paints and plastics. However, its production
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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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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