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research aims to develop new AI for shared human-AI decision-making in healthcare imaging. This post is focused on AI-assisted ultrasound guidance building on the group’s prior work on video and multi
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on transplant using multimodal medical data. You will be responsible for literature review, data cleaning, model development and implementation. You should possess a relevant PhD (or near completion) in
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will be tailored to your expertise, spanning from hardware design to system-level optimization and control methods. For the AI position, you will develop machine learning models that incorporate physical
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developing mathematical algorithms and simulations in MATLAB, in particular with Semidefinite Programming and Sum of Squares and of the analysis and design of feedback control systems using these approaches
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(including a Parenting and Carers Fund and the Carer’s Career Development Fun d), training, and a variety of diversity and inclusion networks. Staff can apply for flexible working to help them balance
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researcher to join the Turing AI World-Leading Fellowship research programme led by Professor Alison Noble. This exciting and ambitious research aims to develop new AI for shared human-AI decision-making in
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to work on meaningful projects with direct clinical relevance. About the role In this role, you will develop and implement computer vision and deep learning algorithms to analyse CT and MRI data from
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(including a Parenting and Carers Fund and the Carer’s Career Development Fun d), training, and a variety of diversity and inclusion networks. Staff can apply for flexible working to help them balance
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research in neuro-symbolic AI, with a focus on using generative AI and prompt engineering as a method to engineer knowledge graphs one can trust. This includes the design of algorithms and architectures, but
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developing mathematical algorithms and simulations in MATLAB, in particular with Semidefinite Programming and Sum of Squares and of the analysis and design of feedback control systems using these approaches