Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- Cranfield University
- ;
- ; University of Birmingham
- University of Nottingham
- ; Swansea University
- ; The University of Edinburgh
- ; The University of Manchester
- ; University of Strathclyde
- The University of Manchester
- University of Manchester
- University of Newcastle
- ; City St George’s, University of London
- ; St George's, University of London
- ; University of East Anglia
- ; University of Exeter
- ; University of Huddersfield
- ; University of Nottingham
- ; University of Warwick
- Durham University
- Imperial College London
- KINGS COLLEGE LONDON
- Loughborough University
- University of Cambridge
- University of Glasgow
- University of Sheffield
- University of Warwick
- 16 more »
- « less
-
Field
-
practices for data processing and integration into hydraulic modelling and risk assessment. This project will create a novel methodology for analysing the datasets to achieve meaningful improvements in flood
-
Deterioration of earthworks slopes (cuttings and embankments), which support transport infrastructure and act as flood defences, is accelerating under increasing weather extremes resulting from
-
United Kingdom Application Deadline 9 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
-
, requiring large computational effort to assess and study system stability. This is becoming even more challenging under increasing complexity requiring detailed dynamical models and with new dynamic phenomena
-
of IR efficiencies like heat pumps. Currently the Standard Assessment Procedure (SAP) attributes infrared heating the same CO2 equivalent as direct electrical heating. However, it is currently unclear
-
within fusion reactors, especially plasma-facing materials (PFMs) exposed to intense heat fluxes and energetic particles. Understanding and predicting how these materials degrade under such conditions is
-
of these assessments can be influenced by factors such as the call handler’s expertise, call volumes, and stress levels, potentially delaying life-saving interventions. Emerging advancements in artificial intelligence
-
challenges in the area of hazard assessment and impact forecasting. The aim of the project is to develop methodologies for forecasting future energy use for various assets and weather scenarios from short term
-
T3 (Applications) through reliable quantum advantage assessment. Project Description The project addresses the critical need for reliable, scalable verification and benchmarking schemes in quantum
-
. The system will leverage cutting-edge techniques in Natural Language Processing (NLP), Machine Learning (ML), and Multimodal Analysis to conduct adaptive interviews, assess candidate responses, and generate