Sort by
Refine Your Search
-
Listed
-
Employer
- University of Bristol
- University of Nottingham
- Durham University;
- Edinburgh Napier University
- Loughborough University
- Loughborough University;
- The University of Manchester
- ; Swansea University
- ; University of Nottingham
- Harper Adams University
- Newcastle University
- Oxford Brookes University
- University of Birmingham
- University of Birmingham;
- University of Nottingham;
- University of Sheffield
- 6 more »
- « less
-
Field
-
) develop novel performance metrics combining accuracy and explainability, to be tested across different AI model types; (2) devise new algorithms for selecting models optimised for holistic performance
-
Computer Science, Mathematics, or related areas. • Strong background in at least one of the following: formal methods, SMT solving, abstract interpretation, or model checking. • Experience with verification tools
-
of contaminated soils on soil strength and erosion control. Developing a Model for the Adoption of Agentic AI in Facilities Management: Enabling Autonomous Decision-Making for Sustainable Built Environments
-
Software Development: Building the Next-Generation Trust Maturity Model Integrating DevOps practices into ML-driven systems: A Framework and Maturity Model for Continuous Machine Learning Development
-
sensing (e.g., PlanetScope, Sentinel-1), advanced numerical modelling (HEC-RAS, Delft-FM), and targeted field surveys to map mining intensity, simulate channel adjustment, and assess changing flood hazards
-
financial economics. You will work at the frontier of interdisciplinary research, using high-resolution flood models alongside property data to build a dynamic picture of where flood hazards are concentrated
-
involve experimental optimisation, leveraging computational tools, statistical modelling, and emerging AI/ML applications to streamline and accelerate the workflow for complex mixtures and metabolomics
-
, and in collaboration with Previsico Ltd. and the US Geological Survey, the researcher will combine fieldwork, remote sensing, and modelling (using CAESAR-Lisflood) to quantify how burned landscapes
-
more frequent and intense extreme rainfall events, creating serious challenges for flood risk management across the UK. Current rainfall datasets are not fit for purpose: radar estimates can be
-
this project unique? You will use cells isolated from human blood and innovative in vivo models in zebrafish to dive deep into the exciting world of RNA biology and immunology, exploring how ELAVL1 regulates