56 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Dr" "FEUP" PhD positions at Newcastle University
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their suitability for real-time emergency decision-making. This project addresses this challenge by combining physics-based modelling with data driven surrogate approaches. The first stage of the project will involve
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important transferable skills that will be highly-desirable in the future process industries. Number Of Awards 1 Start Date 1st October 2026 Award Duration 4 Years Sponsor EPSRC Supervisors Dr Jonathan
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Dr Mathew Barraclough , Prof Anthony O’Neill , Dr Simon Lowes Eligibility Criteria We are adopting a contextual admissions process. This means we will consider other key competencies and experience
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Water Group Supervisors Dr Anna Murgatroyd and Prof Richard Dawson at Newcastle University, Dr Geoff Darch at Anglian Water and Liz Corbett at Northumbrian Water Group Eligibility Criteria An MEng
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apply them to state-of-the-art data from observatories such as the NASA missions NICER, NuSTAR and IXPE. Number Of Awards 1 Start Date 01 October 2026 Award Duration 4 years Application Closing Date 31
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Pharmaceuticals Supervisors Prof. Mike Waring and Dr. Hannah Stewart Eligibility Criteria We are adopting a contextual admissions process. This means we will consider other key competencies and experience
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Date 31st January 2026 Sponsor EPSRC , Eli Lilly Pharmaceuticals Supervisors Dr Hannah Stewart , Professor Mike Waring Eligibility Criteria We are adopting a contextual admissions process. This means we
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Pharmaceuticals Supervisors Prof. Mike Waring and Dr. Hannah Stewart Eligibility Criteria We are adopting a contextual admissions process. This means we will consider other key competencies and experience
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careers in research, industry, or regulation. Number Of Awards 1 Start Date 1 October 2026 Award Duration 4 years Application Closing Date 15 February 2026 Sponsor EPSRC Supervisors Dr Leo Freitas , Dr Ken
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programmed in advance. If anything changes, it may fail. This project explores how to build more adaptable systems using vision-language-action (VLA ) models. These combine computer vision (to see), natural