Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Newcastle University
- Cranfield University
- University of Nottingham
- University of East Anglia
- University of Newcastle
- AALTO UNIVERSITY
- Loughborough University
- University of Birmingham
- ;
- ; University of Exeter
- KINGS COLLEGE LONDON
- King's College London
- University of Birmingham;
- University of Cambridge;
- University of East Anglia;
- University of Glasgow
- University of Warwick;
- ; Loughborough University
- ; Newcastle University
- ; Swansea University
- ; The University of Edinburgh
- ; University of Nottingham
- ; University of Plymouth
- ; University of Southampton
- Cranfield University;
- Hartpury University and College
- Heriot Watt University
- Heriot-Watt University;
- Loughborough University;
- Newcastle University;
- The University of Manchester;
- UNIVERSITY OF VIENNA
- UWE, Bristol
- University of Cambridge
- University of Exeter;
- University of Glasgow;
- University of Hertfordshire
- University of Nottingham;
- University of Sheffield
- 29 more »
- « less
-
Field
-
This PhD project will focus on developing, evaluating, and demonstrating advanced data analytics solutions to a big data problem from aerospace or manufacturing system to uncover hidden patens
-
data, you will develop an AI-driven optimisation framework to identify where such interventions can deliver the greatest combined benefits for people and the environment. The research combines urban
-
to the space-based LISA observatory. The research will advance post-Newtonian waveform modelling through improved analytical techniques, incorporate strong-field information from numerical relativity simulations
-
breeding. The project will involve extensive industry consultation therefore the ideal candidate will be possess strong communication, relationship-building, and analytical skills and be confident working in
-
existing biomedical foundation models (e.g., Med-PaLM) using techniques like Low-Rank Adaptation (LoRA). Big Data Analytics: Managing and analysing complex, multi-modal data from globally significant
-
the research. They will conduct relevant systematic and/or meta-analytic reviews to describe the current literature and inform their research. They will undertake qualitative data collection and analysis and use
-
. Robust evidence is needed to ensure the resilience of flood defences and maintain ecological health. For further information on the project, we will be hosting a ‘Prospective applicant webinar’ at 2:00pm
-
profound interest in inorganic chemistry, both in experimental and modelling applications. We are looking for candidates who are also interested in the analytical and numerical aspects of the work
-
inaccurate, and rain gauge networks, while reliable, are too sparse to capture highly localised storms. Reliable, high-resolution rainfall data is urgently needed to improve flood prediction, climate
-
the Ven Te Chow Hydrosystems Laboratory at UIUC, using 3D-printed riverbed models derived from field data. Finally, insights from experiments will be incorporated into cutting edge flood models to enable