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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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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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genome science, including the development of new algorithms and statistical methods to analyse genome sequencing data. Moving forward, the labs are jointly building an interdisciplinary research team
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pipelines and algorithms to construct and evaluate foundation models for whole-body and abdominal MRI. Alongside this, you will conduct comprehensive and systematic literature and database searches related
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. Currently, patient selection is insufficiently accuracy, our preliminary modelling work suggest that biomechanics modelling can improve this. You will work with clinicians across Europe to test your algorithm
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research for understanding the learned algorithms in brains and machines. The post holder will provide guidance to less experienced members of the research group, including postdocs, research assistants
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classification algorithms including machine learning); and the output data and interpretability. The project “SORS in the community” is funded by the EPSRC (https://www.ukri.org/news/new-tools-aim-to-improve-early
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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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and process their results. Helping to develop new models and algorithms to simulate pulse propagation, the material response, and other aspects of our experiments. Coding in Julia and python. Writing