532 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Universidade de Coimbra" PhD positions in United Kingdom
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and experimental data, the student will develop predictive models of strand displacement reactions in non-ideal settings, in collaboration with the other students within BIOHYBRITE. These areas include
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October 2026 Additional Funding Information This project is fully funded for 3 years. Funding includes tuition fees, an annual tax-free maintenance allowance and a research training support budget.
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fees. See UKCISA for further information. Starting in October 2026. Later start dates may be possible, please contact Dr Lucia Florescu once the deadline passes. You will need to meet the minimum entry
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programme. Nationality restrictions Other eligibility criteria The proposed research project must be within the remit of EPSRC's research themes. Please see EPSRC website for information. Application
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and in-depth information about their vision. This could lead to a paradigm shift for monitoring vision in patients with MS – enabling earlier and more reliable detection of vision-related manifestations
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experimental development at the NQCC. Supervisors: Dr Eran Ginossar and Alexander Owens Entry requirements Open to candidates who pay UK/home rate fees. See UKCISA for further information. Starting in October
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Science, Physics, or a relevant science or engineering related discipline. To apply, and for more information, please contact the main supervisor; Dr Jack Swallow - jack.swallow@materials.ox.ac.uk . Please
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for fuel system applications. While these methods provide a wealth of knowledge and information, they remain impractical for industrial use. Therefore, AI modelling techniques will be harnessed to develop
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should have a strong foundation in artificial intelligence, machine learning, and multi-agent systems, along with experience in programming, data analysis, and model development. Knowledge
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technologies, AI and big data. Crop and soil health - resistance and integrated pest management (including AI-driven prediction) and improving the root-soil interface (carbon, water and nutrient availability