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learning, such as the rapid generation of realistic implant geometries or the learning of biomedical parameters from experimental or clinical datasets. Specific tasks within the project include
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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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for data-efficient exploration and optimization within the process parameter space as well as for adaptive, data-driven machine learning to map the electrolysis process to a digital twin. Data workflows and
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to teach you missing skills during your induction. Our Offer: We work on the very latest issues that impact our society and are offering you the chance to actively help in shaping the change! We support you
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, feminist or queer archives; collaborative platforms such as Wikipedia; or digital memory projects in Central and Eastern Europe. We are also interested in research on the effects of AI on minor languages and
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to build a collaborative scientific carrier in computer science and medical data analysis at a German top-ranked university. Help to acquire, mentor and teach students (e.g., PhD, MSc, BSc, seminar series
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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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(e.g. via machine learning) to qualitative analyses (e.g. via interviews) to support ambitious policies for climate and energy transitions. This position Green hydrogen is key to decarbonizing many hard
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19.07.2022, Wissenschaftliches Personal The Machine Learning and Information Processing group at TUM works in the intersection of machine learning and signal/information processing with a current
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the student solutions using machine learning. We offer: - International and gender-balanced group - Dynamic and collaborative work style - Flexible working hours, home office possibilities etc. - Full-time