32 formal-verification-computer-science Postdoctoral positions at University of London in United Kingdom
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About the Role This Postdoctoral Research Associate (PDRA) position is part of an exciting EPSRC-funded programme, "Enabling Net Zero and the AI Revolution with Ultra-Low Energy 2D Materials and
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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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About the Role Applications are invited for one Postdoctoral Research Associate with expertise in structural biology to join the research group of Aravindan Ilangovan at Queen Mary University
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. As a result, we actively collaborate with experts in Computer Science as part of Royal Holloway’s Centre for AI. In return we offer a highly competitive rewards and benefits package including: Generous
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About the Role The purpose of this role is to provide qualitative and quantitative research support for a research and impact programme on food reformulation. This role sits within the Research and
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the boundaries of neural interface research towards an engineered biology approach. About You The successful candidate will hold a PhD in chemistry, molecular biology, or biomedical engineering (or a related field
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at the Barts Cancer Institute (Queen Mary University of London). This role will involve analysing existing spatial-omics data sets and developing novel computational tools to understand the risk of developing
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View All Vacancies Comparative Biomedical Sciences Location: Hawkshead (nr Potters Bar, Herts) Salary: £39,969 to £50,760 Per Annum Including London Weighting Fixed Term / Full Time Closing Date
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developmental science. The successful candidate will contribute to a major research programme investigating how educational experiences shape mental health from childhood into adulthood. The role involves working
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Vitro Models. The project aims to use organ-on-a-chip technology combined with bioengineering approaches to develop, validate and use a suite of vascularised human tendon-chip models. These high quality