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Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and Control Research Institute at Faculty
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Area Engineering Location UK Other Digital-Twin Technology to Accelerate Development of Electric Propulsion Systems This exciting opportunity is based within the Power Electronics, Machine and
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an independent impact assessment of potential climate interventions in the Arctic marine environment through laboratory experiments and computer modelling. The team will develop physical, climate and ecosystem
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technologies to enhance vehicle performance and safety, including the creation of generalised machine learning training processes. Additionally, AI-driven adaptation strategies will be investigated to enable
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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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, manipulate large datasets, visualise data and perform numerical and statistical analysis is a requirement. Experience in handling 'big data', machine learning and working in distributed teams, is useful
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offers a modular, cohort-based training programme with emphasis on innovation and impact, collaborative working and learning, continuous development, active engagement with partners and stakeholders and
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, distributed ledgers) Desirable: Experience with generative AI (e.g. LLMs) Interest in Human-Computer Interaction Interest in privacy enhancing technologies (PETs) Other: Experience in presenting or preparing
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. Essential skills: A BSc degree or equivalent ideally in a health related field, excellent computer literacy, good inter-personal communications skills. Desirable skills: Previous experience in medical
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electrical machines. Funding is provided for three and a half years covering tuition fees, an enhanced rate stipend and research costs associated with the project. Early application is advised as the position