162 parallel-computing-numerical-methods-"Simons-Foundation" uni jobs at University of Manchester
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together world-leading researchers from a range of underpinning disciplines, including probability and statistics, applied mathematics and numerical analysis, and other areas of computational science. The
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A Postdoctoral Research Associate appointment in numerical modelling of volcanic conduit flow is available from November 2025 for 42 months in the framework of the newly funded NERC Large Grant
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project team to develop an initial VR risk reduction training programme and implementation toolkit, using user-centred design approaches. The project is using a phased, mixed-methods approach to develop
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funded ENLIGHT - Enabling a Lifecycle Approach to Graphite for Advanced Modular Reactors consortium, a £13.2 million, five-year programme accelerating innovation in next-generation nuclear technologies. It
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cultural heritage is mirrored by the achievements of some of the University’s most celebrated names. The computer revolution started here in June 1948 when a machine built by Tom Kilburn and Sir Freddie
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The Division of Informatics, Imaging and Data Science wishes to appoint a Research Associate to an exciting project exploring the creation of models of 3D objects for interactive experiences such as
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discoveries. Manchester’s industrial and cultural heritage is mirrored by the achievements of some of the University’s most celebrated names. The computer revolution started here in June 1948 when a machine
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BACKGROUND This is a research project taken in the Digital Manufacturing Lab led by Prof. Charlie Wang. The project aims to a computational kernel to effectively generate optimised structure and
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computational, molecular and biophysical techniques. During the project you will design the methodology for, and perform the directed evolution of H-transfer enzymes using parallel selection methods, measure
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methods for causality as applied to healthcare. At University of Manchester, our focus in the hub is on how we can develop and apply causal inference for decision support. Therefore, we are interested in