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developing the theoretical and algorithmic foundations of compositional world models. A key application focus of the grant lies in rapid and safe real-world skill acquisition in application domains such as
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” and “wet” lab workflows). You will be able to Design, develop and implement algorithms and systems based on foundation models, large language models and/or AI agents for automated scientific discovery
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ovarian cancer prognosis, COVID-19 prediction, and childhood mental health. You will have (or be close to completing) a PhD in a quantitative discipline such as computer science, mathematics, statistics
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such as UK Biobank. You will design and optimise scalable computational pipelines and algorithms to construct and evaluate foundation models for whole-body and abdominal MRI. Alongside this, you will
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This is an exciting opportunity to help shape the direction of a new research group, and supervise PhDs and Masters’ students. We are looking for an independent postdoc who wants to explore both
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hold, or are close to completing, a PhD in robotics, robot learning, or a closely related field. You possess strong expertise in deep learning and robot navigation, with hands-on experience in deploying
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movement; (iii) generate benefits for both society and the environment by guiding possible mitigation strategies; and (iv) drive technological progress through the development of novel algorithms
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Regularization. We aim to develop mathematical understanding of implicit regularisation properties in deep neural networks to guide the development of algorithmic paradigms aimed at combining statistical
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-ome data at bulk and single cell resolution. You will hold a PhD in Mathematics, Systems Biology or a related subject. Experience with mathematical modelling of dynamical systems using linear and non
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at:*Ji-Seon Kim kim group About you Applicants must hold a PhD in Chemistry or Physics or a related subject area (or be close to completion) prior to taking up the appointment. The project will involve