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by using numerical experiments or formal proof. * Helping adapt and refine existing continued fraction arithmetic algorithms written in C/C++ for use on modern computer hardware. * Performing
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St George’s, University of London is the University of business, practice and the professions and brings together the expertise and excellence of City, University of London and St George’s, University
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this, the Fellow will implement a universal design methodology for such fluids of complex rheology, using a Machine Learning (ML) algorithm to be incorporated in a Computational Fluid Dynamics framework. Training
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Location Tait Building Contract type Permanent and Fixed Term Job category Research Hours Full-time Salary min £43,482 Salary max £43,482 Publication date 12-Sep-2025 Closing date 21-Sep-2025 City St