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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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, scale and resolution in which in vivo pathways of immune cells can be unraveled. Furthermore, it provides a goldmine for training causal machine learning models to move towards precision medicine
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Dynamics, Bioprocess engineering, Data Science, Machine Learning, Computational Chemistry Offer Description MSCA Doctoral Network machinE LEarning for inteGrated and multi-parAmetric eNzyme and bioproCess
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of visualisation, machine learning, and human-computer interaction under the joint supervision of both institutions. The position is shared by TU Wien and USTP and offers the opportunity to conduct research at both
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Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 36-month PhD studentship will contribute to cutting-edge advancements in automated drug discovery through
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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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systems, and space applications. We combine theory, physics-based simulations, machine learning, and autonomous workflows to understand and design materials that can perform under conditions where
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combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real-world energy applications, the project aims to better capture the dynamics of urban infrastructures
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | 13 days ago
Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Are you passionate about Artificial Intelligence, Machine Learning
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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