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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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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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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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motivation. Consistency in meeting deadlines and responding in a timely manner. Innovation: Possession of a natural curiosity to learn and a continual pursuit of personal and professional growth in the field
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License No If yes, what is the required licensure/certification? Required Computer Applications: Microsoft Excel, Microsoft Word, Microsoft PowerPoint, Microsoft Outlook Required Other Computer Applications
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 13 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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Wrocław University of Science and Technology / Faculty of Information and Telecommunication Technology | Poland | 7 days ago
creating a semantic repository for storing and indexing tax documents, designing machine learning algorithms to represent data in embedding spaces, and building tools for semantic search, interpretation
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UNIVERSIDAD CATÓLICA DE MURCIA - FUNDACIÓN UNIVERSITARIA SAN ANTONIO DE MURCIA | Spain | 18 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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been revolutionized in recent years by machine learned interatomic potentials (MLIP), and questions that were impossible to tackle five years ago can now be addressed. The state-of-the-art approach