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Field
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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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, preferably linked to numerical/mathematical modeling or data analysis. High willingness to learn and master novel computational approaches. Collaborative spirit, teamwork, and excellent English skills. We
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management of scientific research and consulting projects. Interdisciplinary collaboration with in-house and external research partners. Prepare your own scientific articles for the academic community
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will apply machine learning — in particular physics-constrained symbolic regression — to discover compact analytical spin-Hamiltonians and their parameter dependencies. These Hamiltonians will feed large
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-throughput experiments in molecular biology, image and video analyses as well as pattern recognition of complex public health data Collaboration in the development of algorithms/methods and development
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and are committed to finding the best candidate, recognizing that growth and learning are part of the role. We expect: the ability to work independently and on your own initiative a methodical and
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sector pay agreement (TVöD EG 13; after interim evaluation TVöD EG 14). The successful candidate will have the opportunity to pursue a habilitation and to teach at the International Max Planck Research
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12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | about 1 month ago
, biology and medicine. Using unique 3D & 4D capture facilities, machine learning, computer vision and advanced graphics, we are modeling every nuance of how humans and animals look and move. We develop
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chemical and/or biological laboratories Ability to work independently as well as collaboratively in an interdisciplinary and international research environment Based on the complexity of the project