73 coding-"https:"-"FEMTO-ST"-"CSIC"-"https:"-"https:"-"https:"-"https:"-"HFML-FELIX" PhD positions in United Kingdom
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‑based work to support model development and validation. The ideal candidate will have a strong quantitative background and an interest in coding and applying modelling approaches to real-world biosecurity
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Apply to Newcastle Portal In ‘Course choice’ tab: Type of Study - ‘Postgraduate Research’ Mode of Study - ‘Full Time’ Year of Entry - ‘2026’ Course code - ‘8440F’ Research Area – Leave Blank Press
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identify your programme of study: Search for the ‘Course Title’ using the programme code: 8856F Leave the 'Research Area' field blank Select ‘PhD in Process Industries; Net Zero (PINZ)' as the programme of
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) Familiarity with image transforms, entropy coding or noise characterisation Funding and Eligibility: Funded PhD. UK Student Supervisors Dr Jay Warnett (WMG) Dr Randa Herzallah (Mathematics)
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Portal Once registered select ‘Create a Postgraduate Application’. Use ‘Course Search’ to identify your programme of study: · search for the ‘Course Title’ using the programme code: 8208F
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Portal Once registered select ‘Create a Postgraduate Application’. Use ‘Course Search’ to identify your programme of study: Search for the ‘Course Title’ using the programme code: 8208F Leave the ‘Research
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the University’s Application Portal: applyto.newcastle.ac.uk In ‘Course choice’ tab: Type of Study - ‘Postgraduate Research’ Mode of Study - ‘Full Time’ Year of Entry - ‘2026’ Course code ‘8370F’ Research Area
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chemistry, modelling, and scientific coding, and who are keen to develop these skills while contributing tools that advance the field and support clean growth and Net Zero technologies. Applicants should have
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Proven record of ability to conduct high quality research in relevant health related subject Previous coding experience (e.g. python, bash, matlab) Good administrative skills, and the ability to organise
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demonstrator for an offshore turbine capable of streaming data and producing CFD‑quality flow and wake fields with ultra‑fast inference. All code, datasets, and reproducible workflows will be openly released