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Field
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geospatial workflows on an abstract level, using purpose-driven concepts and conceptual transformations; develop AI and machine learning based technology to automate the description and modeling of data
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scans and use advanced data-driven methods, including artificial intelligence (AI) and machine learning to improve outcome prediction and patient stratification. deepen our understanding of the etiology
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18 Sep 2025 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Engineering » Computer engineering Engineering » Electrical engineering Physics
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researchers in soft robotics, control theory, and machine learning. They will have access to a fully equipped lab and benefit from collaborations within the ERC team and across TU Delft. There will be
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questions. Given the uncertainties involved in food supply chains, we prefer candidates who have a background in (stochastic) optimization methods (e.g., machine learning, stochastic dynamic programming
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novel materials, tools, or artistic creations, humans instinctively explore the unknown in order to acquire information about it, to make sense of it, to act on it, and to appreciate what is in front of
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technology, computer-aided design, microfabrication and ‑fluidics, culture of human cells, analytical cell and molecular biology techniques, and bioimaging methods. Analytical and proactive – You combine sharp
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Computer Science, Artificial Intelligence, Engineering or a closely related field; Solid background in machine learning and/or evolutionary optimisation; strong programming skills (Python/C++); Proven interest in
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engineering or a closely related field. Hands-on expertise – You have experience with OoC or MPS technology, computer-aided design, microfabrication and ‑fluidics, culture of human cells, analytical cell and
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algorithms) Proficient in English. For information please check the Graduate Schools Admission Requirements. Familiarity or interested in using machine learning is also desiered. TU Delft (Delft University