Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- University of Manchester
- University of Cambridge;
- ;
- ; University of Surrey
- Newcastle University;
- The University of Manchester;
- University of Warwick
- ; Coventry University Group
- ; Imperial College London
- ; The University of Manchester
- Imperial College London
- King's College London Department of Engineering
- The University of Manchester
- University of Birmingham;
- University of Bristol
- University of Cambridge
- University of Derby
- University of East Anglia
- University of Liverpool
- University of Newcastle
- University of Plymouth
- University of Reading
- University of Sussex;
- University of Warwick;
- 15 more »
- « less
-
Field
-
capable of leveraging signals from terrestrial base stations, non-terrestrial networks such as LEO satellite, and complementary on-board sensors. Specifically, it will: To design reconfigurable airborne
-
science interlink prevention and prediction of wildfire risk, by contributing to the development of a fundamental physical model to understand the process of fire spread for wildfires, as part of a European
-
: Working knowledge of MATLAB/Python and signals processing Understanding of electromagnetics Experience with CAD and mechanical design How to apply: Interested candidates should submit a full formal
-
2 Fully Funded PhD Candidate positions in GENIUS MSCA Doctoral Network hosted at University of Derby
a procedure for obtaining refugee status under the Geneva Convention 140 are not taken into account. Exclusivity The candidate must be working exclusively for the action. Selection process Recruitment
-
performance simulation capabilities for gas turbine engines developed at Cranfield University as the starting point. Applications are invited for a PhD studentship in the Centre for Propulsion and Thermal Power
-
contribute to the development of: An R package for path-space rejection sampling for diffusion processes. An R package for Bayesian Fusion pooling inference, such as privacy Bayesian Fusion and constraint
-
Atmospheric Observatory (weybourne.uea.ac.uk ) and the Heathfield Tall Tower in the UK, you will: Disentangle atmospheric signals into anthropogenic and natural processes (1, 2) to quantify ffCO2, making use
-
, please contact the supervisory team directly to find out more and discuss a project proposal before making an application to the lead university. You should indicate clearly on your application which
-
at the interface between stochastic modelling, signal processing and data science. Ultimately, the project will develop key indices that can be used to assess the health of the soil ecosystem. Such indices
-
the interpretability of these models can be enhanced to support clinical decision-making. This project will leverage the complementary expertise of both supervisory teams in EEG signal processing, graph deep learning