86 high-performance-quantum-computing-"https:"-"https:"-"https:"-"https:"-"https:" positions at Imperial College London in United Kingdom
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to develop a performance programme that supports dual-career athletes while at Imperial and maintain a strong performance record across regional, national and international competitions. Level 3 or above
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help create the next generation of doctors and scientists—benefiting patients and populations globally. We are seeking a highly motivated individual to join our team as Programme Administrator
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theoretical and computational analyses of transport and exchange processes using high performance computing, to guide optimisation of cDTI measurements. Research Associate: Hold a PhD in applied computational
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the advert prior to the closing date stated should we receive a high volume of applications. It is therefore advisable that you submit your application as early as possible to avoid disappointment. If you
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researchers and educators to join as visiting academics by appointment through the Provost’s Visiting Professor (PVP) Programme. This is a superb opportunity for academics interested in taking sabbatical leave
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help create the next generation of doctors and scientists—benefiting patients and populations globally. We are seeking a highly motivated individual to join our team as Programme Administrator (MBBS
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of Professor Ed Tate at Imperial College London. This role will support the generation of high-throughput mass spectrometry (MS) data to power state-of-the-art Artificial Intelligence (AI) and Machine Learning
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of Professor Ed Tate at Imperial College London. This role will support the generation of high-throughput mass spectrometry (MS) data to power state-of-the-art Artificial Intelligence (AI) and Machine Learning
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individual to join our professional, busy, and friendly team, to help deliver high-quality programme support. Reporting to the Programme Manager, you will provide excellent administrative support to guarantee
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The role will engage in cutting-edge translational research that develops computational models for assessing cardiac biomechanics and for predicting outcomes in cardiac diseases. This includes (1) a