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numerical simulations and machine learning in order to better understand and characterize active matter systems. A possible direction is to use physics-informed machine learning techniques to connect
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part of a project entitled "Energy Storage as an Enabler of Sustainability through Optimization, Machine Learning, and High-Performance Computing," supported by the Dieter Schwarz Foundation through a
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for a Professorship (W2) (5 years/tenure track) of Statistical and Machine Learning in the Life Sciences, combined with the lead of a research group Computational Statistics & Dynamical Systems for Life
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and (2) develop learning rules that are both technology-feasible and well-suited for machine-learning workloads. The project will consist among others of the following tasks: Investigate and design
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) Implementation and training of an imitation learning model to replicate human delivery manipulations Evaluation of generalization capabilities across different tools and placement locations Testing on the humanoid
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for Philosophy of Machine Learning for Science (m/w/d) to commence as soon as possible. The tenure-track position is embedded in the Cluster of Excellence “Machine Learning: New Perspectives for Science
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Machine Learning Group, Department of Engineering, CambridgeMLG Cambridge About Us News Research Publications People PhD Admissions Blog Latest News Papers with MLG authors to appear at ICML and
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The successful candidate will develop generative machine-learning methods for amorphous molecular thin films — the supramolecular structures that govern the performance of organic-electronic materials
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19.08.2026 Application deadline : 15.11.2026 The Tübingen AI Center invites applications for two tenured full professorships (W3) in Machine Learning and Intelligent Systems (m/w/d), to start as
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Learning commencing on April 1st, 2027. The Junior Professorship in "Probabilistic Methods in Machine Learning" is at the interface of applied mathematics, statistics, and computer science. It is dedicated