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completed, or be close to completing, a PhD/DPhil in a relevant quantitative field together with a demonstrable track record in studying humans and machine learning models. Advanced programming and
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will contribute to the development of a new simulation-based pre-training framework for building more robust and trustworthy machine learning-based clinical prediction models. Funded by the Medical
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projects in computer vision research, with a particular emphasis on Spatial Intelligence, 3D Computer Vision, and 3D Generative AI. You should hold a relevant PhD/DPhil (or near completion*) in Computer
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involve directed evolution and protein optimisation, applying molecular biology and biophysics. Researchers will be supported to develop skills in the latest AI or machine learning tools for protein design
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) a PhD in a quantitative discipline such as computer science, mathematics, statistics, engineering, or a related field. Strong programming skills and experience in machine learning or statistical
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. Proficiency in Python and/or machine learning applications for data analysis. Ability to work independently and manage multiple research activities. Experience contributing to academic publications and
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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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responsibility for carrying out 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
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are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models using multimodal data including neuroimaging
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are passionate about applying machine learning to real-world clinical challenges. The successful candidate will lead the development and validation of predictive models using multimodal data including neuroimaging