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on research, with optional contributions to education and supervision of students. Job requirements You have a master's degree in computer science, artificial intelligence, or mathematics. You can demonstrate
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Description We are looking for a PhD-candidate interested in topics that lie on the border of optimization by the use of heuristic algorithms and (Explainable) Artificial Intelligence ((X)AI). Specifically, in
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Two Postdoctoral Researchers in Cell Delivery-Based Beta Cell Replacement Therapy for Type 1 Diabete
30 years of experience in research and teaching in the fields of Computer Science, Cybersecurity, Artificial Intelligence, Robotics, Data Science, and Applied Mathematics. In this role, you will be
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, potentially complemented by techniques from artificial intelligence. This project is part of the national Add-reAM program, which brings together academic, industrial, and other partners to explore the role
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for PIXEurope: https://www.tue.nl/en/news-and-events/news-overview/05-12-2024-pixeurope-consortium-to-lead-the-european-pilot-line-on-advanced-photonic-integrated-circuits Link for PITC: https://pitc.nl
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organisations. Link for PIXEurope: https://www.tue.nl/en/news-and-events/news-overview/05-12-2024-pixeurope-consortium-to-lead-the-european-pilot-line-on-advanced-photonic-integrated-circuits Link for PITC: https
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Temporary Job Status Not Applicable Hours Per Week 40.0 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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tools – from wikis to robots, Generative Artificial Intelligence (GenAI) introduces new opportunities to assist students working together on creative problem-solving tasks. To fully harness this potential
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, Medicine and Life Sciences at Maastricht University, is recruiting a PhD candidate. The position is embedded in the Materials-Driven Regeneration (MDR) program and focuses on microengineering the next
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, the PhD researcher will develop physiological-model-based artificial intelligence technologies to assess patients’ recovery process, detect or even predict the occurrence of clinical adverse events like