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/antanaviciute-group-computational-biology-and-tissue-immunology We offer • World-leading infrastructure and facilities • Opportunity to learn cutting edge molecular techniques
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Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing research group (CfAM) at the University of Nottingham. The student will work in
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% of their time on teaching/related professional development. Teaching duties will be agreed annually with Programme Directors and tailored to the demonstrator’s expertise and career goals. Applicants will be
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work on the INSTINCT-MB programme, which brings together teams based at Newcastle University, The Institute of Cancer Research and University College London. The programme will generate a wide range of
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://www.bris.ac.uk/pg-howtoapply . Please select Mechanical Engineering on the Programme Choice page. You will be prompted to enter details of the studentship in the Funding and Research Details sections of the form
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through the Researcher Academy’s Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing
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may be possible, please contact Dr Mark Whiting once deadline passes. You will need to meet the minimum entry requirements for our Engineering Materials PhD programme. Candidates must meet Surrey
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; EPSRC Centre for Doctoral Training in Green Industrial Futures | Bath, England | United Kingdom | 3 months ago
biggest environmental challenges? This fully funded PhD offers a unique opportunity to develop energy-efficient, cost-effective, and carbon-reducing manufacturing processes — placing you at the forefront
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The role The post is part of the Wellcome Discovery Award research programme “Collective Action for Race Equity in Health and Social Care”, which aims to address and dismantle structural factors
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of innovative computational methods using Big Data, Behavioural Science and Machine Learning to understand behaviour through the lens of digital footprint/“smart data” datasets, cutting across sectors ranging