74 computer-programmer-"https:"-"CEA-Saclay" "https:" "https:" "https:" "https:" "https:" "UCL" "UCL" uni jobs at Imperial College London
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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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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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enabling the effective leadership and smooth running of the Department of Computing. This is a pivotal, position that supports the HoD, the Department Management Committee (DMC), and the Director of
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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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harness the convergence of AI with other frontier technologies — including quantum computing, engineering biology and advanced materials science. You will play a defining role in positioning Imperial
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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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. 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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to join a multidisciplinary team at the forefront of cancer prevention research. Tailored training programmes to support academic career development. Sector-leading salary and remuneration package
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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