106 engineering-computation "https:" "https:" "https:" "https:" "https:" "https:" "UCL" positions at Imperial College London
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engineering and downstream analytical workflows. While experience in machine learning is welcome, you should have a background in strong data engineering, data management, and analytical skills, and sufficient
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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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The post is within the Thanzi La Mawa programme. The primary objective of this team is to improve population health and reduce health inequalities by helping to enhance the efficiency and equity
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and spinouts with deep technology-based solutions for climate mitigation and adaptation. Encompassing hardware, software and hybrid solutions, the project supports climate-focused businesses across a
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College London is a world-leading university for science, technology, engineering, medicine and business (STEMB), where scientific imagination leads to world-changing impact. Imperial manages one
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and life cycle assessment to understand the business opportunities that may arise. You must hold a Ph.D. in (bio)chemical engineering, (bio)process engineering, biotechnology, chemistry, or a related
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, and collaborative projects. You should have a masters degree or equivalent in Neuroscience, Computer Science, Mathematics, Biomedical Engineering, or a related discipline with a focus on machine
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enabling them to achieve the best outcomes possible, then this role may be for you. You will be working with young people aged 14–19 who are engaged with our Maker Challenge programme within the Dangoor
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in industry-university collaborations and technology transfer and you will be an integral member of Imperial’s Enterprise Division , working with leading global companies and our world class
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. To this end, the project integrates state-of-the-art knowledge from different disciplines such as algebraic topology, differential geometry, machine learning, and computer vision. You will conduct original