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Theme: Energy and Sustainability Project P number: P25303 Start date: 29/09/2025 Studentship funding Sponsored by Sponsored by EPSRC and Hydrogen Waves Ltd., this DTP studentship will provide a bursary of up to £20,780 (tax free) plus fees* for four years. Type of opportunity Eligibility &...
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The Department of Sociology, Social Policy and Criminology at the University of Liverpool in collaboration with ForcesWatch invites applications for this fully-funded ESRC CASE PhD Studentship from the North West Social Science Doctoral Training Partnership (NWSSDTP). This will commence...
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flexible working patterns e.g. part-time working and job share options. Use our total rewards calculator: https://www.hw.ac.uk/about/work/total-rewards-calculator.htm to see the value of benefits provided
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. This project will develop and apply new computational/analytical tools to guide XFEL experiments for specifically tracking lattice fluctuations and ion dynamics in energy materials (batteries). The project will
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Apply online, by clicking the 'Apply' button, above. Select programme type (Research), 2025/26, Faculty of Engineering and Physical Sciences, next page select “PhD Engineering & Environment (Full time
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This 3.5 year PhD project is fully funded and home students, and EU students with settled status, are eligible to apply. The successful candidate will received an annual tax free stipend set at the UKRI rate (£19,237 for 2024/25) and tuition fees will be paid. We expect the stipend to increase...
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This PhD at Cranfield University explores the development of resilient, AI-enabled electronic systems capable of detecting faults and autonomously recovering from failures in real time. The project focuses on AI-driven fault diagnosis, predictive analytics, and embedded self-healing mechanisms,...
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have a leading programme of research into creating synthetic mimics of IBPs, understanding their function, and deploying them in healthcare and biotechnology - for example storing cells and tissue
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create a computational tool based on experimental input, simulated data, and machine learning methodology to extract 3D atomic structure information from 2D identical location STEM images. STEM image data
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Applications are invited to undertake a three-year PhD programme in partnership with industry to address key challenges in manufacturing engineering. The successful candidate will be based