62 structural-engineering "https:" "https:" "https:" "https:" "https:" "https:" "Multiple" "U.S" uni jobs at Imperial College London
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achieve enduring excellence in research and education in science, engineering, medicine and business, for the benefit of society. Our strategy, Science for Humanity, is ambitious and positions Imperial as a
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spans multiple years and involves close coordination between academic units, professional services, digital systems and external requirements. REF 2029 will require the integration of diverse data sources
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. Understanding of the UK school system and the application process to higher education Excellent organisational skills, including the ability to coordinate your own workload, prioritise multiple tasks, and take a
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– this includes Research Software Engineers (RSEs) and technical professionals working in data and computing infrastructure / High Performance Computing (HPC) roles. Led by Imperial College London, the project is
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. CADI is supported by the UK Department for Science, Innovation and Technology with a remit to develop science-policy interfaces to aid the adoption of transformative AI applications across the UK
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As a Research Associate in Data-Driven Optimisation, you will work at the interface of chemical engineering, machine learning and automation, to develop next-generation workflows for the design and
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delivery of high-quality communications, engagement and marketing activities across the Department of Chemical Engineering. This varied role will contribute to the production of digital content, delivery
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. Experience providing high-quality administrative or operational support in a professional or academic environment. Strong organisational skills with the ability to manage multiple tasks, prioritise effectively
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course design in Medical Education, including awareness in current trends and challenges. Possess excellent project management skills and are proficient in managing multiple workflows in a
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candidates will be involved in projects exploring novel ways to incorporate topological structures into deep learning pipelines, contributing to both theoretical advancements and practical applications