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PhD Position on Machine Learning Detection of Positive Tipping Points in the Clean Energy Transition
Infrastructure? No Offer Description Develop machine learning models to detect early signs of abrupt shift towards clean energy technologies and make climate action adaptive to this information. Job description
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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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. 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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and master’s degrees, Professional Learning & Development programmes, and interdisciplinary research themes – including Emerging Technologies & Societal Transformations, Resilience, Smart Industry
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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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16 Jan 2026 Job Information Organisation/Company Eindhoven University of Technology (TU/e) Research Field Computer science » Computer architecture Computer science » Computer hardware Researcher
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machine learning packages (e.g.PyTorch). Completed academic courses in AI or machine learning. Interest in societal, ethical and philosophical questions. We consider it an advantage if you bring one or more
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., high performance, functional array programming DSLs) to tackle challenging probabilistic and differentiable programming applications (e.g., experimental design, machine learning for science). We do so by
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interest in interdisciplinary research at the intersection of AI and neuroscience (NeuroAI), and human vision; A background in machine learning, deep learning, and/or representational alignment research
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is made for you! Information We invite highly motivated students with a strong background in mathematical control theory, and a keen interest in machine learning to apply for the PhD position within