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apply ultra-fast machine-learning interatomic potentials (UFPs, Xie et al., npj Comput. Mater., 2023, 10.1038/s41524-023-01092-7 ) for long, multi-million-atom molecular dynamics (MD) simulations
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to the student and administrative/faculty members as appropriate. Other duties as assigned by the program administrator. Basic knowledge of technology-mediated platforms for blended learning and computer software
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23 Dec 2025 Job Information Organisation/Company ETH Zürich Research Field Architecture » Other Engineering » Civil engineering Engineering » Other Researcher Profile First Stage Researcher (R1
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medical device environments is highly valued. PhD in computer science, electrical engineering, biomedical engineering, cybersecurity, or a closely related field Strong record of peer-reviewed publications
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catalysts for the synthesis of a range of industrially valuable compounds. This PhD project is part of the Horizon Europe Marie Sklodowska-Curie Action (MSCA) doctoral network (DN) ELEGANCE (machinE LEarning
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. In addition, you must have: a solid foundation in energy technology and a strong understanding of artificial intelligence (AI), machine learning (ML), and data-driven modeling documented experience
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and/or the CAD/CAM process is a plus. I am proficient in Python and am familiar with data science and machine/deep learning toolkits. As a PhD researcher at KU Leuven, I perform research in a structured
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having a focus and in-depth expertise in a particular topic mentioned above. Applicants should have a PhD in Computer Engineering, Computer Science, or Electrical Engineering. Expertise in Quantum Physics
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candidate in the exciting area of multiscale and multiphysics modelling of sustainable fibrous composites, with additional focus on uncertainty quantification and machine learning. Information The context
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subsequent PhD in computer science, engineering, biophysics, applied mathematics, computational biology or a related field Proven programming expertise in Python (PyTorch, scientific Python) with solid