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devices that rely on superior thermal insulation to deliver energy. Applicants should hold, or are expected to achieve, a 1st or 2:1 honours degree in Materials Science or Chemistry To apply, please contact
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there are special terms that apply to the project, these will be discussed with Candidates at Interview and fully set out in the offer letter. Full details will be confirmed at offer stage.
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Background Access to healthcare is an ever-increasing global issue. Over 15% of the current global population require rehabilitation care, but the majority of them do not receive healthcare access
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current best-in-class benchmarks. Beyond the automotive sector, the project might also contribute to our understanding of how other spaces can be designed to support the required user experiences
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Fixed-term: The funds for this post are available for 12 months A position is available for a Postdoctoral Research Associate (Postdoc) in the forthcoming Aspirational Computing Lab in
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treatment, material and energy flow analysis, integrated data modelling, systems dynamics modelling, circular economy, sustainability assessment performance, decision-support tool design Month when Interviews
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Computational verification of high-speed multi-material flows, where physical experimentation is highly limited, is seen as critical by the defence Sector (source: the UK Atomic Weapons
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objects, by embedding them into a 2 or 3-dimensional space through a representation learning algorithm, has been widely used for data exploratory analysis. It is particularly popular in areas such as
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(bursary) starting from approximately £23,000 plus payment of their full-time home tuition fees for a period of up to 48 months (4 years). Lean automotive aluminium with a lower concentration of alloying
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for PFAS removal using rapid small-scale column testing (RSSCT). Evaluate the influence of contact time, media type, and multi-stage configurations on treatment efficacy. Characterise the scientific