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Field
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follow specialized training programs (e.g. ARENA). Specific Requirements Knowledge: Linear algebra, probability and statistics. Graph theory and algorithms on graphs. Machine learning and deep learning
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. As a PhD researcher, you will unravel the atomic-scale mechanisms of hydrogen embrittlement in compositionally complex recycled steels, using density functional theory and machine-learned interatomic
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, computational biology, statistics or a closely related field. You have strong programming skills, preferably in Python, and experience with machine learning or deep learning. Experience in computer vision
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, data science, or related - Strong programming skills (Python and/or R) - Experience with machine learning or data analysis - Knowledge of deep learning frameworks Application Procedure Interested
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applications for machine learning. Technology Assessment: Evaluate emerging technologies, instrumentation devices and other tools related to power electronics for electric vehicles applications. Collaboration
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development support to help you plan your next career step. At HST, our values – Share. Care. Dare. – shape the way we collaborate, support one another and create knowledge with societal impact. Learn more
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career step. At HST, our values – Share. Care. Dare. – shape the way we collaborate, support one another and create knowledge with societal impact. Learn more about the department on our website and in
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compositionally complex recycled steels, using density functional theory and machine-learned interatomic potentials, in close collaboration with leading academic partners and Tata Steel. Job description At TU Delft
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, research institutes, industry, public agencies, and leading global institutions. We welcome motivated applicants in robotics, control, AI, machine learning, physics, and related fields, including early-stage
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, control, AI, machine learning, physics, and related fields, including early-stage researchers eager to contribute to this emerging scientific frontier. About the project The role of the PhD candidate will