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About the project: Machine learning accelerated electronic transport calculations for complex materials Supervisor: Prof. Neophytos Neophytou, University of Warwick Advancements in materials
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want to develop machine learning approaches that not only withstand adverse conditions but actively learn from their own failures – and can you back those systems with rigorous formal guarantees? We
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AI and data science, particularly in dynamic settings where observations are collected sequentially and decisions influence future outcomes. This project will develop novel machine learning and
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29th June 2026 Languages English English English The Department of Mechanical and Industrial Engineering has a vacancy for a PhD Candidate in Machine Learning Approaches to Conservation Condition
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is seeking a PhD student to join an ongoing Royal Society–Research Ireland University Research Fellowship project focused on Machine Learning for the Design of Additively Manufactured Two-Phase Heat
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In 2026, UniSQ will offer the UniSQ Incarcerated Student Learning Resource Scheme to support incarcerated students who are commencing or continuing an undergraduate program at UniSQ, by assisting
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Heidelberg Institute for Theoretical Studies (HITS gGmbH) | Heidelberg, Baden W rttemberg | Germany | about 3 hours ago
) in Geometric Deep Learning to join the Machine Learning and Artificial Intelligence (MLI) g roup to perform research in geometric deep learning for materials science. This research is part of
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A Doctoral Researcher (PhD student) in Machine Learning for Electron–Phonon Interactions and Wannier-Based Hamiltonians Aalto University is where science and art meet technology and business. We
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Norwegian University of Life Sciences (NMBU), within the Faculty of Science and Technology(REALTEK), invites applications for a PhD position in Applied Causal Machine Learning. The position is affiliated with
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The continuous release of Earth Observation (satellite) data and the emergence of Machine Learning methods open up new possibilities for understanding forests. These large datasets provide