70 computer-programmer-"https:"-"FEMTO-ST" "https:" "https:" "https:" "https:" "UCL" uni jobs at Imperial College London
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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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experiences. As a Placement and Internship Adviser, you will combine relationship management, student support, operational planning and programme delivery to ensure these opportunities are high-quality, well
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with Imperial’ s Strategy: Science for Humanity . You will broaden Imperial’s research capabilities, complementing our existing strengths. You will build on a successful programme of engagement and
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Funded by a Royal Society Faraday Discovery Fellowship, you would be working on the project "Predicting synthesisable materials: bridging the gap between computation and experiment", working
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of contact for all stakeholders, and will be central in incubating a collaborative and collegial multidisciplinary culture. You will have the ability to manage a varied and busy programme of activities with a
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London, the University of Oxford, and GSK to establish a world-leading hub for model-informed medicine. You will also be working alongside Prof Steven Niederer’s computational and Prof Saman Sadiquis
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multidisciplinary environment. Ability to use a variety of software to plan, evaluate and present data with clarity and accuracy. The opportunity to continue your career at a world-leading institution and be part of
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. Grow in your career with tailored training programmes for academic staff including dedicated support with navigating your career and managing research as well as a transparent promotion process. Sector
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of a variety of programmes and initiatives that engage young people under the age of 18. This role will support young people from a wide variety of backgrounds, from the UK and worldwide, to access and
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datasets and tools. While the role is computational, you will work closely with experimentalists and engage with real industrial case studies, ensuring that developed methods are robust, interpretable and