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programming task within the thematic context of the advertised position: https://www.hpc.uni-wuppertal.de/de/peter-zaspel/challenge-in-bi-molecular-machine-learning/ Employment conditions This is a
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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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the reference number 27697, via our online portal: Apply now via https://jobs.uksh.de/job/Kiel-PhD-%28mfd%29-Statistical-Genetics-Machine-Learning-Schl-24105/1279933701/ For more information visit: www.uksh.de
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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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the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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want to hear from you! Your Job: Work on a wide range of computer vision and machine learning methods and applications focusing on the aspects outlined above, inspired by the needs of societally relevant
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by colloids, as well as methods for immobilizing these ions. Modern methods of theoretical chemistry (first principles, kinetic Monte Carlo, machine learning) will be applied to investigate diffusion
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Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use machine learning (ML) along with data from previously solved problem
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/fractionalized phases of matter, via computational many-body physics nonequilibrium quantum dynamics, to quantum computation, quantum information, and machine learning. The Institute provides a stimulating