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of multi-fidelity and active learning strategies for molecular systems. The candidate will collaborate in an international research team on related research questions in machine learning, uncertainty
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– from the modeling of material behavior to the development of the material to the finished component. PhD position on physics-based machine learning modeling for materials and process design Reference
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the development and application of probabilistic inference methods and machine learning techniques for quantitative uncertainty modeling and for the integration of heterogeneous climate data
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international collaboration with mentors from the USA, Asia, and Europe. TUD and the RTG embody a university culture that is characterized by cosmopolitanism, mutual appreciation, thriving innovation and active
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digital age” drives collaboration with academic and nonacademic partner institutions in the Hamburg Metropolitan Region and around the world. We would like to invite you to be part of our community to work
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international collaboration with mentors from the USA, Asia, and Europe. TUD and the RTG embody a university culture that is characterized by cosmopolitanism, mutual appreciation, thriving innovation and active