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parameters based on paired visible-light and X-ray images. The developed techniques will be validated on real data. As a candidate, you must have a strong background in machine learning and computer vision, as
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always held a central role in applied mathematics and, nowadays, its popularity has surged in fields traditionally focused on real-world applications, such as engineering, machine learning and imaging
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Mathematics (Inverse Problems), Computer Science (Machine Learning, Computer Vision, Efficient Algorithms and High-Performance Computing), and Physics (Image Formation Modelling). Your project is part of
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28 Feb 2026 Job Information Organisation/Company Delft University of Technology (TU Delft) Research Field Engineering » Computer engineering Engineering » Simulation engineering Researcher Profile
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organizational skills. Experience with using machine learning packages (e.g.PyTorch). Completed academic courses in AI or machine learning. Interest in societal, ethical and philosophical questions. We consider it
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. You have familiarity with multivariate methods, network analysis or machine learning. You have interest in language, cognition, and individual variability in brain organisation. What we offer you We
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. Methodological Approach Candidates will develop and apply state-of-the-art machine learning techniques, including deep learning, representation learning, variational autoencoders, and graph-based models. A strong
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in the new Lab42 building at the Amsterdam Science Park. The VIS Lab performs research on deep learning and computer vision, from hyperbolic learning to medical imaging and from NeuroAI to foundation
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and scalable. Design and build a technology demonstrator prototype of clinical-testing grade. Collaborate with interdisciplinary teams, including clinicians, engineers, and machine learning (ML) and
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the Computer Engineering group. Curious to learn more about the project, and perhaps our group? Feel free to browse our webpages: About our department: QCE department . About our group: Computer Engineering Lab