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start dates: 1 October 2025 (Enrolment open from mid-September) Supervisors: Hari Arora (Biomedical Engineering), Richard Johnston (Materials) and Iain Whitaker (Medicine) Aligned programme of study: PhD
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You will join the EPSRC-funded project “Behavioural Data-Driven Coalitional Control for Buildings”, pioneering distributed, data-driven control methods enabling groups of buildings to form
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Position Summary: Applications are invited for a PhD studentship, to be undertaken at Imperial College London (Control and Power Research Group, Department of Electrical and Electronic Engineering
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Development of novel processing techniques Modelling techniques that can inform the direction of experimental activity Physical, mechanical and materials characterisation techniques Data-driven approaches
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information on the admissions process generally, please visit our How to Apply for a Research Degree webpage or contact the Doctoral College . Applications will not be considered if information is missing
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://www.lboro.ac.uk/international/applicants/english/ ). Funding information: Studentship type – 50% external partner matched with 50% University. The studentship is for 3 years and provides a tax-free stipend of
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programme’ page, please select (Neuroimaging) Research MPhil/PhD (Full-time). More information on the department and the programme is available at the departmental prospectus page here: https://www.kcl.ac.uk
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Research Assistant/Associate in Photonics Integration of Graphene and Related Materials (Fixed Term)
investigate the large area production of graphene, BN, MoS2 and other layered materials, optimize their transfer process in view of their application in energy, electronics and photonics. This will include
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, via the admissions portal (accessed via the 'Apply' button above) by midnight (23:59 GMT), 19th August 2025. On the ‘Choosing a programme’ page, please select (Neuroimaging) Research MPhil/PhD (Full
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, while simulations are subject to error due to uncertainty in nuclear data and unresolved physical processes e.g. thermal expansion and fine-scale inhomogeneities. Generating independent simulation