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tools like FEniCS and Python. Additionally, working on a high-impact, interdisciplinary project will strengthen problem-solving, critical thinking, and project management skills. The collaboration with
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& Presentation Skills, preparing research for high-impact journals and international conferences Along with transferable skills in project management, technical writing, teamwork and public engagement, graduates
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PhD Studentship: Electrical Machine Architectures for Next-Generation NetZero E-Mobility. the University of Nottingham This project offers an exciting opportunity to undertake cutting edge research
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. The studentship will commence from September 2025 onwards, under the supervision of Dr Rebecca Baggaley and Dr Johan H Thygesen (IHI, UCL), Dr Rachel Burns (Institute of Epidemiology and Health Care, UCL) and Prof
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2025 Reference: RD-PHD-02-LS-MH-25 Project Title: Dietary strategies to reduce methane production in dairy cows and their effects on the rumen microbiome and metabolism Primary supervisor: Prof. Liam
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for health and wellbeing. Successful students will work on projects that aim to make a real difference for affected communities, by investigating challenges including but not limited to aging populations
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
design, commissioning, assembling and optimization of new growth/production and transfer equipment. Such devices will then be used in a wide range of applications such as on-chip optical routing, flexible
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risk for future cardiac events. This project is in partnership with Liverpool Heart and Chest Hospital (LHCH). The successful PhD candidate will benefit from working with a multidisciplinary team in
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seeking an academic career in primary care cancer diagnosis, or in data analytics more generally. Main duties and responsibilities Undertake doctoral research on pancreatic cancer diagnosis Finalise project
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& robust control, and learning for dynamics & control. The main task of the PhD student will be to develop sound data-driven methodologies for learning control policies with provable guarantees