361 computer-programmer-"Multiple"-"Prof"-"FEMTO-ST-institute"-"U"-"O" PhD positions in United Kingdom
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Field
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, interpretable models from experimental and operational data. The core goal is to balance model accuracy with computational efficiency, while meeting the needs of experimental validation. The framework will
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technologies, bulk and single-cell RNA-sequencing, flow cytometry, multiplex immunofluorescence, and standard molecular biology and biochemistry techniques. A computational component may also be available
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About the role We are seeking a talented Postdoctoral Researcher with expertise in healthcare AI to join the Modernising Medical Microbiology (MMM) Unit at the University of Oxford. This is an exciting opportunity to lead innovative research at the interface of AI and clinical medicine, working...
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computational and machine learning approaches to integrate Oxford Nanopore (ONT) long-read data with bulk and single-cell RNA-seq profiles. The aim is to identify host-microbiome molecular signatures that drive
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Applications are invited for a PhD studentship in the Department of Computer Science at City, University of London. The successful candidate will work on developing a novel AI-powered conversational
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) publication at top tier ranked international conferences and journals in Computer Science. Person specification: MSc in Computer Science or AI (minimum of 2:1 degree or higher) UK home student status holder
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Technology, The University of Nottingham. Applicants are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in on-platform manufacturing engineering. The
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This PhD project aims to reduce—by approximately an order of magnitude—the time and computational effort required to evaluate point-defect energetics in technologically important mixed-anion
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Funding: School of Computer Science Studentship consisting of the award of fees, together with a tax-free maintenance grant of £20,780 per year for 3.5 years. Lead Supervisor’s full name & email
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spaces and habits for them. This is a highly interdisciplinary project that combines computational modelling and behavioural science. The first part will be based on the use of state-of-the-art