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The Role Join our growing team to help re-architect and re-implement the University’s research virtual machine (RVM) and high-throughput computing (HTC) platforms. Beyond provisioning and
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commitment to widening opportunity through the power of education and contributing our talents to creating a fairer world, and a more prosperous region. We are putting inspirational learning and impactful
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of antiviral host-mechanisms and comparative virology datasets, including those derived from transcriptomics experiments. The role will also involve the application of machine learning approaches to virus
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students. The computer revolution started here in 1948 when a machine known affectionately as ‘The Baby’, ran its first stored program. The celebrated wartime codebreaker Alan Turing worked on this computer
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. The task of the theory group led by Prof Kyriienko at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will
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both to those with a research background and to those with legal practice or teaching and learning experience who will be able to contribute and lead on our co-curricular offering to students. Those
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a useful reconstructed image by employing a suite of AI/machine learning tools with limited impact on the task dependence. Specifically, the successful candidate will develop models and methodologies
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teach postgraduate students who are well motivated to develop their English language and academic literacy skills conduct online tutorials, attend staff meetings and standardisation sessions (both in
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, you will work closely with our technical and academic colleagues to shape the delivery of practical hands-on learning experiences for students on our specialist programmes. You will be supporting
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is funded by EPSRC, titled “Adopting Green Solvents through Predicting Reaction Outcomes with AI/Machine Learning”, involving academic investigators from 3 institutions (Imperial College London