Sort by
Refine Your Search
-
Listed
-
Category
-
Program
-
Employer
- ;
- University of Sheffield
- University of Oxford
- Cranfield University
- University of Cambridge
- UNIVERSITY OF SOUTHAMPTON
- University of Birmingham
- University of Nottingham
- ; The University of Manchester
- KINGS COLLEGE LONDON
- UNIVERSITY OF VIENNA
- University of Bristol
- University of Glasgow
- Durham University
- Imperial College London
- Nottingham Trent University
- University of Manchester
- ; University of Leeds
- AALTO UNIVERSITY
- DURHAM UNIVERSITY
- Heriot Watt University
- King's College London
- Loughborough University
- Nature Careers
- Swansea University
- UNIVERSITY OF SURREY
- University of Newcastle
- ; Manchester Metropolitan University
- ; Newcastle University
- ; University of Birmingham
- ; University of Nottingham
- ; University of Surrey
- ; University of Warwick
- Aston University
- Birmingham City University
- Cardiff University
- City University London
- Lancaster University
- Manchester Metropolitan University
- Ulster University
- University of Bath
- University of Leicester
- University of Surrey
- Wenzhou Business College
- ; Anglia Ruskin University
- ; Aston University
- ; Cranfield University
- ; Imperial College London
- ; Swansea University
- ; UWE, Bristol
- ; University of Bristol
- ; University of East Anglia
- ; University of Essex
- ; University of Oxford
- ; University of Southampton
- ; University of York
- Arden University
- Glyndwr University
- Kingston University
- Medical Research Council
- Newcastle University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- The University of Southampton
- University College London
- University of Liverpool
- University of London
- University of Northampton
- University of West London
- University of Winchester
- University of the West of England
- 60 more »
- « less
-
Field
-
conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
-
, algorithm development, AI, and machine learning, supporting fusion energy engineering through advanced simulation and workflow optimisation. You will work on impactful, collaborative projects across academia
-
formulation, which displays striking similarities to that used by the Computational Fluid Dynamics (CFD) community, has inspired the investigators to adopt conventional CFD algorithms in the novel context
-
Engineering, Mathematics, Statistics, Computer Science or conjugate subject; strong record of publication in the relevant literature; good knowledge of machine learning algorithms and/or statistical methods
-
computational algorithms of different datasets, and implement novel algorithms within the framework of existing code, providing documentation and user support. You will be responsible for leading statistical
-
novel multi-objective optimisation algorithms, to evaluate metrics such as material circularity, system efficiency, cost, and carbon footprint. The University of Surrey is ranked 12th in the UK in
-
work with researchers on the DASS programme to develop and promote freely available software, implementing new statistical methods and algorithms for identifying anomalous structure in stream settings
-
position will work with researchers on the DASS programme to develop and promote freely available software, implementing new statistical methods and algorithms for identifying anomalous structure in stream
-
the coordination of large-scale robot systems (ground and aerial). The ideal candidate will possess hands-on experience with designing and implementing reinforcement learning algorithms, and deploying them onto real
-
pivotal role in analysing large-scale genomic and clinical data, applying cutting-edge algorithms, and collaborating with renowned experts in the field. At PBCI, we believe in fostering a collaborative and