646 web-programmer-developer "https:" "https:" "https:" "UCL" "UCL" PhD positions in United Kingdom
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to leverage molecular dynamics simulation develop methods to determine the partitioning with relevant surfactant systems. The project will further be extended to studying the interaction of different additives
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recommend that you apply early as the advert may be removed before the deadline. This fully funded PhD position, offers an exciting opportunity to develop and optimize multiscale models for surfactant
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cell failure and its implications for system-level battery design. By creating a new scientifically robust framework to assess and mitigate thermal runaway, this PhD project will develop a unique
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-for-profits, technology providers, and universities - to identify relational strategies that foster sustainable and circular practices. The successful candidate will develop deep expertise in building B2B
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developing better models for fragmentation of metals that include a consideration of the structure at the micro-scale, linking this to fragment formation at the macro-level. This will build on work in crystal
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Learning as well as an ability to develop, build and test interactive systems. Funding Comment: Covers full tuition, £20,780 stipend (2025/26), plus up to £1,000 yearly for research costs.
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to enhancing workforce diversity. We actively seek to attract, develop, and retain colleagues with diverse backgrounds and perspectives. We welcome applications from all genders/gender identities, Black, Asian
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-grade experience that employers value. The journey You'll develop machine-readable privacy rules, build core functionalities that audit and explain data-sharing decisions, prototype agent systems showing
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Met’s Doctoral College community, benefiting from specialist training, collaboration opportunities, and professional development. This is an exciting opportunity for a motivated researcher passionate
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modelling frameworks to provide detailed characterisations of design conditions for large scale turbine arrays. The developed models and understanding will be used alongside standard flow models and as input