Sort by
Refine Your Search
-
Listed
-
Employer
- ;
- University of Birmingham
- Imperial College London
- Nature Careers
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- UNIVERSITY OF SOUTHAMPTON
- KINGS COLLEGE LONDON
- King's College London
- University of Leeds
- University of Nottingham
- CRANFIELD UNIVERSITY
- The University of Southampton
- QUEENS UNIVERSITY BELFAST
- Queen's University Belfast
- University of Bristol
- University of Cambridge
- University of London
- University of Oxford
- ; King's College London
- ; University of Oxford
- ; University of Southern Denmark
- Birmingham City University
- Manchester Metropolitan University
- UNIVERSITY OF MELBOURNE
- UNIVERSITY OF SURREY
- University of Glasgow
- University of Lincoln
- University of Liverpool
- University of Manchester
- University of Sheffield
- University of Surrey
- 21 more »
- « less
-
Field
-
. The researcher would be expected to have knowledge of protein structure, protein ligand binding, machine learning and expertise in workflow development. Information generated by the project will be widely
-
engineering science, with knowledge and/or some experience of energy technology and policy; and/or quantitative analysis including econometrics, statistics and machine learning and related disciplines handling
-
to) fundamental research in machine learning or statistics, algorithm design, the application of AI methods in science, healthcare, social sciences, or business. You should have a PhD or equivalent level of
-
annotation of these metabolomes using multistage fragmentation (MSⁿ) data, incorporating novel computational methods and strategies (e.g. spectral matching, network-based approaches, machine learning) where
-
will a have a relevant PhD and medical degree alongside registration with the GMC at Specialist Registrar Garde or below. You will have a recent track record in histopathology and use of machine learning
-
using hybrid models combining mechanistic, GenAI, and machine learning approaches. You’ll contribute to building disease-specific Digital Twins using large-scale single-cell multi-omics datasets
-
. The Department seeks candidates with interests in Statistical research at the interface of machine learning and AI. They will have the skills and enthusiasm to lecture graduate level, over a wide range of topics
-
time role, 0.1FTE. The activities of this role will support development of future proposals for funding, into AI for renewable energy. You will consider ways in which the integration of machine learning
-
Strong analytical skills and experience in developing and implementing machine learning/AI solutions using relevant languages and frameworks Excellent communication skills and proven ability to collaborate
-
seeks candidates with interests in Statistical research at the interface of machine learning and AI. They will have the skills and enthusiasm to lecture graduate level, over a wide range of topics within