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Join our multidisciplinary research team to develop and apply machine learning and bioinformatic algorithms in biomedical research. This PhD project will focus on developing machine learning
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become the bottleneck in achieving optimal performance and trustworthiness. This project will focus on how a federated multi-task learning framework can be effectively designed and optimised to address
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to date focus on just one layer, understanding what keeps AF going is challenging. This PhD project aims to bridge that gap by combining advanced machine learning tools with a new experimental protocol
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of this WASP-financed project is machine learning, in particular dealing with generative models and instabilities associated with cycles of retraining on mixtures of human and machine-generated data
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. This project will rely on recent advances in neural networks to develop machine learning potentials (MLPs) for MD simulations of realistic nanomaterial/coolant-liquids and use these to gain fundamental insights
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and machine learning to tackle the complexity of force allocation and motion planning under uncertainty and actuator failures. The project combines theoretical research in stochastic optimal control
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Centrum Wiskunde & Informatica (CWI) has a vacancy for a 4-year PhD position (m/f/x) on the subject of Fundamental Techniques in Table Representation Learning in collaboration with the University
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solutions need to be safe and accurate. Aim This project will focus on investigating and developing new ways in which deep learning-based solutions can continuously learn and deal with unseen situations, with
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A continual learning approach for robust robotic control in electric batteries assembly. This project is an exciting opportunity to undertake industrially linked research in partnership with
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at the intersection of machine learning, bioinformatics, and computational pathology. Project Overview: Integrating histopathological imaging with omics (e.g., transcriptomics, genomics, proteomics) holds tremendous