Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- Cranfield University
- ; Swansea University
- ; The University of Manchester
- University of Nottingham
- ; EPSRC Centre for Doctoral Training in Green Industrial Futures
- ; Newcastle University
- ; University of Leeds
- ; University of Southampton
- ; University of Sussex
- ; University of Warwick
- University of Newcastle
- ; Imperial College London
- ; University of Birmingham
- ; University of Bristol
- ; University of Cambridge
- ; University of Exeter
- ; University of Nottingham
- ; University of Reading
- AALTO UNIVERSITY
- Harper Adams University
- Imperial College London
- University of Cambridge
- 13 more »
- « less
-
Field
-
optimise a ‘Digital Twin’ of the Tees estuary to ensure that the NBS are deployed at locations optimal for performance and longevity while operating within the constraints placed upon deployment by other
-
workshops as a means to continuously improve technical and theoretical knowledge. Ability to obtain information from literature and from colleagues and integrate this into developing and optimizing work
-
more adaptable to other chiral systems. Understanding how these two systems can be optimized and integrated, including effective solvent exchange and recovery, is crucial. Efficient solvent management is
-
investigate how to optimize the "athlete-equipment-playing environment" interface, integrating state-of-the-art profiling technologies. The research will adopt an individualised sport approach, targeting up
-
genomic investigation of their demise in the UK. This will involve optimizing WGS sequencing protocols for working on museum specimens and developing best practices for museum metagenomics. We will focus
-
effects of NSPs on poultry performance. Locally sourced ingredients are becoming more prevalent, challenging some of the traditional enzyme strategies in regard to substrate presence and ultimately, optimal
-
designing and developing experimental equipment suitable for containing the liquids at the temperatures needed, as well as optimizing the quality of the data obtained, both through experiment design and
-
, and more efficient operations. After all, the greenest energy is the one that’s not spent – and this project aims to unlock just that by refining the way we design and optimize airfoils. The focus
-
that values equity, diversity, and inclusion, gaining unique expertise in aerospace systems design and integration (airframe, engine, subsystems), system of systems optimization, multi-fidelity models
-
optimization of batteries against the swelling phenomenon. This project aims at developing scientific machine learning approaches based on the Bayesian paradigm and electrochemical-thermomechanical models in