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. Performs other duties as assigned. Minimum Qualifications Requires concentration and strong attention to detail. Basic computer skills required and desire to learn new skills on the job. Must be able to lift
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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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, Mechanical), Computer Science, Applied Math/Statistics, Physics—or related. Candidates who will graduate in the near future are also welcome to apply. Strong foundation in machine learning/deep learning and
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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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and optimize their properties for neuromorphic computing through combined electrical and MOKE measurements, and train them to achieve artificial intelligence tasks. - Micromagnetic simulations - machine
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seeks a distinguished scholar for a faculty position at the Full Professor level. The ideal candidate will be at the forefront of research that integrates modern machine learning methods with economic
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Responsibilities: Teach selected graduate courses within the multidisciplinary masters degree programs. See website for details of programs: http://www.coe.neu.edu/graduate-school/multidisciplinary Responsibilities
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 14 days ago
machine learning, 3D visualisation and real-time images (augmented reality). The main robot will the Tiago++, by PAL Robotics, which is a modern omnidirectlonal, bimanual robot. With the help of a PhD
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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | about 9 hours ago
infrastructure you will have the opportunity to make an important contribution for a healthier society. The Theis Lab has a long-standing reputation for pioneering machine learning and AI methods in molecular
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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