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heavily relies on empirical determination of key model parameters. By combining protein structure descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange
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optical communication networks and systems, as well as machine learning, computer vision and compressing digital videos. The Applied Machine Learning (AML) group is part of the Department for Artificial
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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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machine learning for practical implementation. Our group studies natural and designs artificial cognitive systems, researches their relationships and develops methods that enable interactions between them
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, machine learning, energy technology or related subjects Prior experience in building predictive models using regression techniques, neural networks (CNN, GNN) or symbolic regression Experience in
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) Intense interaction with consortium Your Profile: Master and PhD degree in materials science, physics, chemistry, informatics, machine learning, energy technology or related subjects Prior experience in
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using X-ray and neutron scattering. One of the research areas is the development of machine learning (ML) based approaches to efficient analysis of the vast data amounts generated in the scattering
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Future. Discover. Together. The Computer Vision & Graphics group of the Vision & Imaging Technologies (VIT) department is looking for a student assistant in the area of deep learning for scene
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11.12.2025 Application deadline: 15.02.2026 The Faculty of Science at Tübingen University invites applications for a W3-Professorship in Machine Learning in Physics at the Department of Physics (m/f
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Faculty of Life Sciences - Department of Biology Research fellow (m/f/d) in the field of Machine learning and Biomedicine with expected full-time employment - E 13 TV-L HU (third-party funding limited until