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research teams led by Prof Knight, and Prof Screen working collaboratively at Queen Mary. The PDRA will interact with a team of academics, PDRAs, and PhD students, working on related organ-chip models, as
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-based workshops; and System Dynamics Modelling, to understand how to maximise the contribution of Nature Based Solutions to climate change adaptation in the UK through multifunctional landscapes in
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-based workshops; and System Dynamics Modelling, to understand how to maximise the contribution of Nature Based Solutions to climate change adaptation in the UK through multifunctional landscapes in
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have a PhD and track record in either computer science with specialisation in relevant AI technologies for surrogate modelling, or in Earth or Environmental Science with a strong track record in
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You will have a PhD in Computer Science or a related discipline or will have obtained it by commencement of the position. Successful candidates will have experience of model training methodologies
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PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods to analyse datasets Experience in statistical or scientific programming (ideally R and/or
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are looking for candidates to have the following skills and experience: Essential criteria PhD qualified in mathematical, physical or computational sciences Experience in using machine learning methods
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experience in: Deep learning Medical imaging computing (preferably neuroimaging) Computationally efficient deep learning Deep learning model generalisation techniques. Translating deep learning models
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. About You The successful applicant will have, or soon obtain, a PhD degree in mathematics or related, or equivalent level of professional qualifications and experience, with expertise in at least one of
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rigorous, collaborative research aligned with project goals. Develop and apply deep learning models, particularly in computer vision, NLP, and multimodal systems. Publish in peer-reviewed journals and