Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Nottingham
- ; The University of Manchester
- ; Swansea University
- ; University of Leeds
- ; University of Sheffield
- ; University of Southampton
- Abertay University
- University of Cambridge
- ;
- ; Durham University
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Loughborough University
- ; University of Birmingham
- ; University of Bristol
- ; University of East Anglia
- ; University of Plymouth
- ; University of Reading
- ; University of Sussex
- ; University of Warwick
- University of Newcastle
- 11 more »
- « less
-
Field
-
networks by analyzing their dynamical systems and probabilistic asymptotic behavior, improving and generalizing diffusion-based generative AI using insights from numerical and stochastic analysis, and making
-
predictions to conventional continuum predictions to understand the relationships between the different theoretical frameworks. The analysis will be accompanied by detailed numerical computations in
-
modelling. Objectives The primary objective of this PhD project is to quantify raindrop-freezing fragmentation using a cloud chamber and support these findings with numerical modelling. Specific aims include
-
on numerical aspects of the network model analysis. Being part of the wider Mathematical Neuroscience research theme within the School of Mathematical Sciences which currently includes 7 members of academic
-
in inks, surfactants added to crop sprays to improve jetting, wetting, adhesion, and bodily fluids with polymeric components. This PhD project aims to explore how such additives affect micromechanics
-
and experience required to perform the role are an aerothermal PhD with a combination of experimental, numerical and low order modelling experience. The PhD must be completed or near completion, and
-
, engineers, and the general public Qualifications Research Assistant Degree in engineering or numerate subject (e.g., mathematics, physical sciences, computer science) PhD close to completion in field of Power
-
, manipulate large datasets, visualise data and perform numerical and statistical analysis is a requirement. Experience in handling 'big data', machine learning and working in distributed teams, is useful
-
repair and maintenance of gas turbine engines. Applicants are invited to undertake a fully funded three-year PhD programme in partnership with Rolls-Royce to address key challenges in soft robotics
-
-suited. By the end of the PhD, the candidate will have gained strong skills in experimental mechanics, test management, materials characterization, and numerical modeling, particularly finite element