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- Eindhoven University of Technology (TU/e); Published yesterday
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: machine learning or deep learning (e.g. PyTorch) scientific data pipelines or large datasets knowledge graphs or structured data systems GPU or distributed computing scientific machine learning or physics
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skills: Good knowledge of ML/AI based techniques to develop fast surrogates (deep neural networks) and capability to develop own efficient model learning schemes (deep learning techniques, representation
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languages, for example Python, and general purpose deep learning frameworks, such as Tensorflow or PyTorch; The interest and ability to share knowledge with other ESA organisational units. You should also
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from the areas of few-shot learning, continual learning and modular deep learning, as well as different LLM alignment frameworks, based on reinforcement learning and direct preference optimisation
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perception systems, using deep learning and simulation-to-real domain adaptation techniques. You will work with a multidisciplinary team, contributing to fundamental and applied research. Your role will
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, interdisciplinary project. At the end of the project, you will have: a deep understanding of the hydrodynamic processes that control the dispersion of buoyant macroplastic items in the coastal zone; expertise in
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-purpose deep learning frameworks, such as PyTorch; An interest in and ability to share knowledge with other ESA organisational units. You should also have good interpersonal and communication skills and
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equipment readiness Contribute with new ideas, coordination and editing scientific proposals for new funding opportunities. The mission of the Department of Electrical Engineering is to acquire, share and
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16 Jan 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Educational sciences » Education Educational sciences » Learning studies Engineering
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fair consideration. Challenge. Change. Impact! Faculty Mechanical Engineering From chip to ship. From machine to human being. From idea to solution. Driven by a deep-rooted desire to understand our