Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- ;
- University of Nottingham
- UNIVERSITY OF SOUTHAMPTON
- University of Birmingham
- KINGS COLLEGE LONDON
- King's College London
- Nature Careers
- UNIVERSITY OF SURREY
- University of Oxford
- Imperial College London
- Queen's University Belfast
- The University of Southampton
- University of Exeter
- University of Leeds
- University of Liverpool
- CRANFIELD UNIVERSITY
- Cranfield University
- EMBL-EBI - European Bioinformatics Institute
- Manchester Metropolitan University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- UNIVERSITY OF STRATHCLYDE
- University of Bristol
- University of London
- University of Manchester
- University of Salford
- University of Sheffield
- University of the West of England
- 17 more »
- « less
-
Field
-
10 minutes and machine learning algorithms to deliver quantitative diagnosis without destroying the samples. The AF-Raman prototype will be integrated and tested in the operating theatre
-
(particularly under extreme conditions), and/or the use of machine learning for solid mechanics/stress analysis problems are encouraged to apply. The job description presented here is deliberately broad due
-
Language Processing (NLP) with a focus on large language models, deep learning, and multi-modal machine learning. The researcher will work on the project KAMAL Health: Knowledge-Augmented Multi-Modal Arabic LLMs
-
quantitative and digital methods, such as descriptive/inferential statistics, data modelling, machine learning (ML), experimental prototyping and technology ideation. A significant degree of autonomy is required
-
the University's research culture and collaborative profile. Qualifications: PhD in Computer Science/AI or a closely related field. Extensive research experience in machine learning, deep learning, and self
-
two issues: (1) It aims to develop new technical instruments to diagnose the quality of machine learning (ML) decisions; identify its failures; and identify root causes of such failures; and (2) it aims
-
development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning algorithms might support the wider integration of, and uptake
-
perform geomechanical analyses of their reservoirs and caprocks. These mechanical earth models will be used to develop an innovative Machine Learning approach to open access data from the North Sea
-
, science and the economy. The postholder will be responsible for undertaking research in generative AI and machine learning methods for audio generation and audio-related multimodal content generation
-
and the economy. The postholder will be responsible for undertaking research in generative AI and machine learning methods for audio generation and audio-related multimodal content generation, including