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-body physics nonequilibrium quantum dynamics, to quantum computation, quantum information, and machine learning. The Institute provides a stimulating environment due to an active in-house workshop
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Your Job: In this position, you will be an active member of the SDL “Fluids & Solids Engineering” and will collaborate strongly with the SDL “Applied Machine Learning”. You will have the following
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models, which are essential for understanding climate change impacts. The work involves reviewing existing modeling and model–data fusion techniques, and developing faster, machine-learning–based tools
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data. Building on these results and codebases, the successful candidate will work on a bioinformatics and machine learning research project on the inference of alternative splice forms using deep
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triggered 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
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-learning–based segmentation, species classification and lineage tracking workflows for multi-species time-lapse data Optimise models and pipelines for real-time performance, enabling adaptive imaging and
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of Mathematics and Natural Sciences at Heinrich Heine University Düsseldorf is inviting applications for the position of a Professorship for Machine Learning (open rank: W2 or W1 with tenure track to W2
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Programme? Not funded by a EU programme Reference Number Bu- CIW 06 Is the Job related to staff position within a Research Infrastructure? No Offer Description WHAT TO EXPECT You will teach mathematics in
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TO EXPECT In the context of this professorship, you will teach and conduct research into drive systems at the Department of Mechanical Engineering, focusing on hydraulic, pneumatic and electric drive systems
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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