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Computation and Data Driven Design of Materials for Onboard Ammonia Cracking This exciting opportunity is based within the Advanced Materials Research Group at the Faculty of Engineering which
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propulsion. Who we are looking for We are looking for enthusiastic, self-motivated applicants with first-class degree in electrical engineering, Aerospace Engineering or Computer Science with good electrical
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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
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-developed research support base including NET2Zero CDT, and EPSRC Centre for Doctoral Training in Resilient Chemistry: Feedstock to Function. The research programme will use a mixture of computational
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Training Programme, those based within the Faculty of Engineering have access to bespoke courses developed for Engineering PGRs. including sessions on paper writing, networking and career development after
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candidates with: • Relevant subject matter experience at required level (e.g. 2.1 or above undergraduate degree in physics, mathematics or computer science) • Willingness to adapt and work across different
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placement during your third year. Standard Programme Requirements Applications are invited from students with backgrounds in Bioscience, Biochemistry, Microbiology, Biotechnology, Environmental Science, Plant
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computer literacy, good inter-personal communications skills. Desirable skills: A Master in Health Economics with experience in cost effective analyses. Funding notes The three year studentship covers UK
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PhD Project: Advanced 3D/4D-Printing of Responsive Biomaterial Devices Applications are invited for a PhD project within the University of Nottingham’s Faculty of Engineering, in the Centre
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PhD Project: 3D-Printed Drug Delivery “Microbots” for Personalised Healthcare Applications are invited for a PhD project within the Faculty of Engineering, in the Centre for Additive Manufacturing