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publications prior to the panel interview. In addition to further excelling your skills in Computer Vision/Big Data/Machine Learning analyses, this opportunity enables you to: - Work closely with clinicians
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of an extension, subject to funding. You will apply and develop cutting-edge machine learning methods to integrate and analyse multi-omic data to identify disease phenotypes. A key aspect of the role is to bridge
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across tissues, over time and upon perturbation for translational benefit, leveraging tissue profiling through multiomic technologies in conjunction with cutting-edge computational and machine learning
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programming languages is required, and experience with the current ATLAS software, computing and particularly the tracking software would be particularly desirable. Experience with machine learning and
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-scale, diverse datasets using machine learning and AI techniques. Findings will be disseminated through peer-reviewed publications, conference presentations, and public engagement. About You You will hold
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, machine learning, governance and operations, we aim to address the complex challenges and opportunities of space exploration. CfAI is a large research group in the Department of Physics at Durham University
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. Desirable experience in AI-assisted image analysis, machine learning, computational modelling, or building predictive models from biological imaging or cell–material interaction datasets. Strong experience in
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-scale, diverse datasets using machine learning and AI techniques. Findings will be disseminated through peer-reviewed publications, conference presentations, and public engagement. About You You will hold
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, machine learning, governance and operations, we aim to address the complex challenges and opportunities of space exploration. CfAI is a large research group in the Department of Physics at Durham University
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strands. • Bespoke modelling of tumour metabolic function using 3D and 4D imaging data • Cancer patient risk prediction using machine learning (with experience in particular in radiomics and transcriptomics