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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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awareness These funded PhD scholarships are suitable for students with a background in Computer Science, Mathematics, Engineering and Cognitive Science. Students with interests in machine learning, deep
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evaluation, but we are primarily looking for a candidate with a strong background in computer science, artificial intelligence, applied mathematics, applied physics, or a closely related field, and with a
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Ph.D. Programme with specialization in Economics, which trains students to engage in high quality scientific research, making use of economic theory and state of the art econometric methods
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learning pipelines for multilayer segmentation and nanoscale transistor classification from microscopy images; (b) Designing graph-based inference models capable of reconstructing higher-level logical blocks
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leader is Associate Professor Soledad Gonzalo Cogno. About the project The successful candidate will contribute to the development of mathematical and computational models to enquire about the mechanisms
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) Developing deep learning pipelines for multilayer segmentation and nanoscale transistor classification from microscopy images; (b) Designing graph-based inference models capable of reconstructing higher-level
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of interest, e.g. the spectral density of strongly correlated models, as measured in ARPES. • The mathematics of the approach will require a lot of innovative developments too. In the only published article
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26 Sep 2026 Job Information Organisation/Company Shibaura Institute of Technology Research Field Technology Engineering Architecture Mathematics Chemistry Geosciences Astronomy Physics Researcher
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project Can AI interpret graphs like a human materials scientist that relates diagrams to composition temperature, pressure, synthesis, processing and uncertainty? The PhD candidate will develop and