262 parallel-computing-numerical-methods-"Prof" positions at University of Manchester
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Programme Exceptional starting annual leave entitlement, plus bank holidays Additional paid closure over the Christmas period Local and national discounts at a range of major retailers As an equal
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The School of Engineering has an opportunity for a Research Associate, working with Prof Cise Unluer, to make a leading contribution to ongoing projects involving the integration of industrial
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, and the impact future network designs may have on the models and control. The PDRA will work under the direct supervision of Prof. Barnes and Dr Preece. The wider supervisory team also includes Prof
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and transformative innovation policy. What you will get in return: Fantastic market leading Pension scheme Excellent employee health and wellbeing services including an Employee Assistance Programme
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This 3-year research associate position forms part of an EPSRC Prosperity Partnership between The University of Manchester and healthcare provider Bupa. The research programme aims to address
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, which you will lead, under the supervision of Prof David Wedge. Collectively, the team has expertise in the analysis of multilevel omic and imaging data; data integration and machine learning; and risk
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, Warwick University and University College London. The research programme aims to address the sustainability of engineering plastics across the transport, electronics and construction sectors by exploring
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-computed tomography (microCT) analysis methods that reveal the 3D structure and evolution of microstructure of concrete non-destructively will be developed within the National X-ray Computed Tomography
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on producing a range of biosurfactants and biopolymers for potential application in sustainable vaccine formulations. Overall Purpose of the Job This post requires the PDRA to design and execute a programme of
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this project we will develop a novel experimental system that is complex yet tractable, enabling rich, coordinated multi-omics analysis coupled with computational modelling to deliver deep mechanistic insight