24 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "https:" "UCL" PhD positions at The University of Manchester
Sort by
Refine Your Search
-
paragraph about your motivation to study this PhD project. The supervisor profiles: https://bernardomagri.eu/ https://borisfouotsa.com/
-
Application deadline: 30/06/2026 Research theme: Applied Mathematics, Continuum Mechanics, Nonlinear PDEs How to apply: https://uom.link/pgr-apply-2425 UK only due to funding restrictions. The
-
guest exchange (J. Am. Chem. Soc. 2025, 147, 17201 https://doi.org/10.1021/jacs.5c02868 ). It is the aim of this project to use this novel methodology to investigate a range of single crystal-to-single
-
to changing internal states and external environmental conditions. Both traditional model-based approaches and modern learning-based control techniques will be employed to achieve an appropriate trade-off
-
for translational biocatalysis, addressing critical needs in the development of sustainable biotechnologies. The programme will equip PhD students with advanced expertise in enzyme science, machine learning, enzyme
-
they can reliably, affordably, and fairly support a net-zero energy system. The research will focus on how data-driven and machine-learning-based control can coordinate demand, storage, and local generation
-
overseas. Training can be provided in computational fluid dynamics, machine learning, and nonlinear dynamics. These skills are highly valued across a wide range of industries. Recent data reveals that Fluid
-
group 14/15-element bond formation. In addition to the wide range of transferable skills developed during a PhD, the appointed researcher will learn and use: (i) Schlenk and glove box techniques; (ii
-
to acquire strong transferable skills (e.g. science communication skills developed by presenting results in group meetings and at national/international research conferences). Applicants should have or expect
-
reusable plaque–flow atlas. Key objectives include to: Develop automated computer aided design (CAD) and meshing pipelines to generate a library of arterial geometries representing common geometric