79 high-performance-quantum-computing-"https:"-"https:"-"https:"-"https:"-"https:" positions at University of Liverpool
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This role provides a rare and exciting opportunity to join a motivated and innovative team of academics, committed to the delivery of high-quality healthcare education and discipline related
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Grade C or above (or equivalent) including English Language, with high level IT, communication and organisational skills. Experience of Microsoft Office is essential and experience of University IT
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The School of Computer Science and Informatics is seeking to appoint an individual to work on rigorous methods to address the risks of generative AI systems. The primary focus will be on techniques
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anniversary in 2031, the University of Liverpool is proud to launch the second cohort of our prestigious Research Fellowship programme, a cornerstone of our Strategy 2031 vision. We are seeking Research Fellows
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anniversary in 2031, the University of Liverpool is proud to launch the second cohort of our prestigious Research Fellowship programme, a cornerstone of our Strategy 2031 vision. We are seeking Research Fellows
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funded by ESRC¿s Smart Data Research UK (SDR-UK) programme. The Imago data service is a collaborative effort led by the University of Liverpool, Newcastle University, and Harvard University, and aims
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programme in the Department of Primary Care and Mental Health, playing a key role in shaping the next generation of clinical psychologists while advancing your own research within a supportive
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anniversary in 2031, the University of Liverpool is proud to launch the second cohort of our prestigious Research Fellowship programme, a cornerstone of our Strategy 2031 vision. We are seeking Research Fellows
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, to ensure that projects and works are delivered to the agreed programme, budget and quality, working to recognised standards. The role will report to the Head of Design Group. This is an exciting role
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Computer Science, Chemistry, Chemical Engineering, Physics, or Materials Science. You will develop optimisation and machine-learning algorithms for human- and literature-informed discovery of new materials