30 computational-"https:"-"https:"-"https:"-"CIPMM---Systemic-Neurophysiology" PhD positions at The University of Manchester
Sort by
Refine Your Search
-
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
-
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
-
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
-
Application deadline: All year round Research theme: Computational Mechanics/Applied Mathematics How to apply: uom.link/pgr-apply-2425 This 3.5-year PhD project is fully funded and home students
-
-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
-
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
-
, computer science, or a closely related discipline (typically first-class or high 2:1, or equivalent; Master’s welcome) • Strong programming skills (for example Python, MATLAB, C/C++) • Strength in at least two of
-
computational protein design to develop new biocatalytic methods for asymmetric synthesis. This collaborative project will leverage the pyridoxal phosphate (PLP)-dependent enzyme UstD, previously developed
-
instruments, large-scale datasets, and an international research community. Training on neutron scattering techniques will be provided. The project is ideal for students who are interested in computational
-
infrastructure. The successful candidate will benefit from access to extensive expertise across The University of Manchester in civil engineering, structural engineering, fire engineering, computational modelling