Sort by
Refine Your Search
-
Listed
-
Category
-
Country
-
Employer
- ;
- University of Birmingham
- Nature Careers
- University of Nottingham
- University of Leeds
- University of Oxford
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- UNIVERSITY OF SOUTHAMPTON
- Imperial College London
- CRANFIELD UNIVERSITY
- KINGS COLLEGE LONDON
- University of Cambridge
- University of London
- King's College London
- UNIVERSITY OF MELBOURNE
- University of Glasgow
- University of Sheffield
- Queen's University Belfast
- The University of Southampton
- City University London
- UNIVERSITY OF SURREY
- ; Technical University of Denmark
- Brunel University
- Cranfield University
- QUEENS UNIVERSITY BELFAST
- University of Bristol
- University of Exeter
- University of Manchester
- University of Surrey
- University of the West of England
- ; University of Exeter
- ; University of Nottingham
- ; University of Oxford
- ; University of Warwick
- Birmingham City University
- Cardiff University
- Durham University
- London Institute for Mathematical Sciences
- Manchester Metropolitan University
- Nottingham Trent University
- Nuffield College
- Plymouth University
- Sheffield Hallam University
- Technical University of Denmark
- University of Brighton
- University of Leeds;
- University of Leicester
- University of Lincoln
- University of Liverpool
- University of Stirling
- 40 more »
- « less
-
Field
-
, including conventional medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and
-
+ inclusion (Stonewall Diversity Champion) and as a Disability Confident employer. We are proud signatories of the Armed Forces Covenant and welcome applications from service people. Further information Before
-
will receive: Generous annual leave: 35* Days Annual Leave (pro rata if part-time) plus Bank Holidays* & Closure Days* Generous pension scheme Cycle to Work & Electric Car Scheme Employee Assistance
-
working with NLP in general and LLMs in particular. They will also help to further develop machine learning models to predict clinical outcomes. Familiarity with current methods in this area is essential
-
(STFC, Daresbury), Prof. Jonathan Tennyson (University College London) and Prof Michael Charlton (Swansea). The Research Fellow will work on the development of methods and computer programs adapted
-
are proud signatories of the Armed Forces Covenant and welcome applications from service people. Further information For further information please contact Jordi Solana, e-mail j.solana@exeter.ac.uk
-
. Our pre-covid NSS scores for overall satisfaction was above 90% for eight years and since covid have been ahead of the sector average and sector benchmarks. We provide a learning experience of the
-
the potential to impact on protected groups and take appropriate action. Desirable Skills: Experience with machine learning or natural language processing. Knowledge of econometric methods for policy evaluation
-
are proud signatories of the Armed Forces Covenant and welcome applications from service people. Further information For further information please contact Jordi Solana, e-mail j.solana@exeter.ac.uk
-
: To create a world class visitor and learning experience across all V&A sites and collections. Focus and deepen the relevance of our collections to the UK creative and knowledge economy. Expand the V&A's