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Generative machine learning models have made significant progress in recent years. Typical examples include, for example, high-quality image or video generation using diffusion models (e.g
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) Theoretical machine learning development – Designing new AI algorithms with broad applications, potentially extending beyond medicine. Our work includes explainable AI, AI in robotics, and geometrical modelling
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Are you looking for a PhD position where you develop state-of-the-art machine learning methods for the life sciences (geometric deep learning, transformer-based approaches, ...) with a focus on
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& machine learning
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patients with mood disorders, including familiarity with clinical assessments (e.g., K-SADS, SCID) Computing and software skills in multiple platforms are helpful as well as familiarity with statistical
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on the intersection between diffeomorphic models of shapes, related geometric theory, and statistics and machine learning, e.g. generative models. Examples of specific topics in this span include Bayesian models
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, their achievements and productivity to the success of the whole institution. At the Faculty of Computer Science, Institute of Artificial Intelligence, the Chair of Machine Learning for Robotics offers a full-time
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Master’s degree in a relevant discipline (cognitive neuroscience, neuroscience, computational neuroscience, psychology, cognitive science, machine learning/data science/AI). Start date: 1 October 2025
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studies in a federated environment. Collaborate closely with colleagues in cryptography, machine learning, and bioinformatics to create innovative approaches that ensure data confidentiality and scalability
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This forward-looking PhD project merges performance science with advanced data analytics and machine learning to further enhance performance prediction in elite rugby union. The successful candidate