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Field
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(AI) or closely related topics in computer science, mathematics, or physics, a thorough understanding of reinforcement learning, fluency in English. The ideal candidate: is interested in working in a
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, from fellow academics to patients. You have experience with analysis of sensor data. You have an affinity for patient care and are able to communicate with patients. You have a good command of written
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which research focuses mainly within the research programmes (1) Algebra, Geometry and Mathematical Physics, (2) Pure, Applied and Numerical Analysis, and (3) Stochastics and (4) Discrete Mathematics and
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Engineering, Medical Image Analysis, Applied Mathematics or a related field Experience with deep learning for image analysis, preferably in medical imaging Experience with generative modelling, ideally
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global scale. That is why we invite you to apply. Your application will receive fair consideration. Challenge. Change. Impact! Faculty of Electrical Engineering, Mathematics and Computer
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framework of the Postdoc position, in alignment with the broader Vidi project; conducting high-quality empirical research (archival research and cultural analysis); contributing to the development of a theory
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perspectives and backgrounds. The Faculty has six departments: Biology, Pharmaceutical Sciences, Information & Computing Sciences, Physics, Chemistry and Mathematics. Together, we work on excellent research
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matter, or polymer physics Enjoy quantitative analysis and physical interpretation of experimental results You are fluent in English and able to collaborate intensively with internal and external parties
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sensitive to researchers’ needs and constraints? You will be part of a project that addresses these questions by combining policy analysis, behavioral research, and stakeholder co-creation. You will map
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observability, potentially integrating physics-aware constraints and generative modelling approaches. Both tracks interact closely to create a data–model feedback loop, enabling systematic analysis of how