Sort by
Refine Your Search
-
Category
-
Employer
- University of Warwick;
- University of Nottingham
- The University of Manchester
- AALTO UNIVERSITY
- University of Warwick
- Newcastle University
- University of Birmingham
- Manchester Metropolitan University
- UNIVERSITY OF VIENNA
- Abertay University
- Durham University
- Imperial College London
- Manchester Metropolitan University;
- University of East Anglia
- University of Exeter
- University of Sussex
- King's College London
- King's College London;
- Newcastle University;
- Northeastern University London
- Oxford Brookes University
- Swansea University
- University of Cambridge
- University of Manchester
- University of Plymouth
- University of Sheffield
- University of Sheffield;
- University of Surrey
- 18 more »
- « less
-
Field
-
Despite significant advances in numerical techniques and computing hardware, the high computational cost of large-scale 3D computational fluid dynamics (CFD) modelling remains a major challenge. A
-
modelling, field experimentation, and hydrothermal analysis. Numerical simulations will be carried out using FEFLOW (or COMSOL/alternative) to represent coupled heat, flow, and transport processes in
-
reservoir heterogeneity. This project will integrate core observations, wireline logs and seismic data to develop geological and petrophysical models that constrain reactive reservoir simulations
-
quantification, and structural surrogate frameworks based on Artificial Intelligence. You will develop tools that bridge from detailed simulation to rapid predictions, compute structural sensitivities, address
-
Northeastern University London Fully Funded PhD Scholarship in Computer Science Reliable Quantum Statistics Northeastern University London > Computing, Mathematics, Engineering & Natural Sciences
-
-Sailors) network, funded by the Marie Skłodowska-Curie Actions (MSCA) Doctoral Network Programme. The E-Sailors network is designed to train the next generation of Electric solar wind sail (E-sail
-
4-year PhD fellowship in the Research Programme - Deep Learning-Accelerated Crystallography Pipeline
determination by developing mathematical methods and integrating machine learning into crystallographic workflows. The successful candidate will develop theoretical and computational approaches to improve
-
computational simulation, supported by experimental investigations using test welds and novel material characterisation methods. This project is available from 1st October 2026. Applications are accepted until
-
combination of field linguistics, acoustic analysis, experimental linguistics, computational simulation, typology, and the historical-comparative method. The project is based jointly at the University of Surrey
-
computational simulation, supported by experimental investigations using test welds and novel material characterisation methods. This project is available from 1st October 2026. Applications are accepted until