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of computational and behavioural neuroscience with modelling and domestic chicks’ data. This position is funded by a Leverhulme Trust project entitled “Generalisation from limited experience: how to solve
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of computational and behavioural neuroscience with modelling and domestic chicks’ data. This position is funded by a Leverhulme Trust project entitled “Generalisation from limited experience: how to solve
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associated computing code for modelling avian influenza outbreaks in Great Britain (GB). One position will focus on modelling the risk of virus invasions into GB in different locations and at different times
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challenge. We seek a senior computational biologist to apply these extensive in-house datasets toward the development of novel, domain-tailored machine-learning models and analytical methods. You will explore
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). The post is funded by NIHR and is fixed-term for 24 months, with a possible extension. This project is about creating novel AI models to predict patient outcomes following acceptance or refusal of an offer
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informal event – you can drop in at any time. Background To create and contribute to the creation of knowledge by undertaking a specified range of activities within an established research programme and/or
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are carried by electrons) and biological systems (where signals are carried by ions). This research will cover theoretical models at many scales including electron dynamics, soft-matter physics, materials
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solutions informed by the latest ideas in medical imaging AI, computer vision and robotic guidance; and evaluate models in simulated and real clinical scenarios. Evaluation may involve quantitative studies
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About the Role We are seeking a researcher for a new programme focused on improving understanding of cancer risk and developing novel multicancer risk prediction models to support cancer prevention
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scientific oversight from Oxford Principal Investigators and GSK scientists, the centre will initially focus on some of the following thematic areas: • Decision analysis under model misspecification