27 computer-programmer-"https:"-"CEA-Saclay"-"https:"-"https:"-"https:"-"https:"-"NOVA.id" PhD positions at The University of Manchester in United Kingdom
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before the deadline. Computational haemodynamic modelling provides a powerful framework for linking blood flow dynamics with cardiovascular disease, using in silico approaches to systematically study flow
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in the groups of Dr Florence Hardy and Prof Anthony Green, University of Manchester, as part of the cross-institutional BioAID Doctoral Training Programme, including world-leading experts from Queen's
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Characterize the molecular basis of enzyme function with spectroscopic, kinetic, and structural techniques. About the programme Join experts in industry and academia working to sustainably manufacture
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up to a £5k/annum research training support grant for the full duration of the 4-year programme. Metal-ligand multiple bonding is a burgeoning area for making chemically novel structural motifs
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motivated students, and EPR/MOF experts. As part of the project, the student will receive training in EPR, NMR, XRD, XPS, TEM. The PhD programme incorporates strong career development elements enabling
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an emphasis on reaction development and optimization. Training BioProcess aims to train the next generation of bio-innovators. Our interdisciplinary programmes prepare PhD students and researchers with the real
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undertake an interdisciplinary programme combining polymer synthesis, materials characterisation, rheology and mechanical testing, and in vitro drug release studies, supported by quantitative analysis and
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in porous geological formations. The successful candidate will develop and implement computational models, validate them against experimental or field data where available, and contribute to the design
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that you apply early as the advert may be removed before the deadline. This PhD project aims to develop a virtual tabletting laboratory by creating computational models that capture the multiscale mechanics
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-driven model selection, and deep learning for data analysis and feature extraction from characterisation data. Surrogate modelling will be employed to reduce computational costs, and AI-based uncertainty