731 systems-science "https:" "https:" "https:" "https:" "Univ" PhD positions in United Kingdom
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systems. The project is jointly supervised with the Law and Technology Research Centre in the School of Law, reflecting a strong interdisciplinary focus on responsible and accountable deployment
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), accounting for dynamic aeroelastic stability at the early design stage has become essential. However, considering flutter constraints in high-fidelity aerostructural optimisation routines is challenging
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allowance of £21,805 (2026/27 UKRI rate). An additional allowance will be provided to contribute towards consumables, equipment, and travel related to the project. Overview ReNU+ is a unique and ambitious
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The Faculty of Science AI Doctoral Training Centre (AI DTC ) invites applications from Home students for fully-funded PhD studentships to carry out multidisciplinary research in the world
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on the study of the digital traces we left behind to capture human behaviour and social dynamics through the lens of Network Science, Complexity Theory, and Data Science. The team is made up of researchers in
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development, modelling and simulation, through to fabrication and advanced optical/electrical characterization—offering a unique opportunity to push the boundaries of photonic device engineering. This is a 3.5
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the professional, ethical, organisational and work-related challenges surrounding the adoption of AI technology for human selection and evaluation. The research is expected to adopt an interpretivist, social
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How to apply: uom.link/pgr-apply-2425 This 3.5-year PhD studentship is open to Home (UK) students. Exceptional overseas candidates can be considered on a case by case basis. The successful candidate
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representatives. The post-holder will have access to a range of data resources to inform the model, including blood donor cohorts from the COMPARE, INTERVAL and STRIDES studies. It is anticipated the work will
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EPSRC funded UDLA PhD studentship. The studentship will start on 1st October 2026. Project Description The project aim is to develop novel FETs and biosensors based on Graphene and 2D Materials