Sort by
Refine Your Search
-
Listed
-
Employer
- ;
- University of Birmingham
- Imperial College London
- UNIVERSITY OF SOUTHAMPTON
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of Nottingham
- CRANFIELD UNIVERSITY
- KINGS COLLEGE LONDON
- King's College London
- Nature Careers
- Queen's University Belfast
- The University of Southampton
- University of Oxford
- Brunel University
- University of Bristol
- ; University of Cambridge
- Birmingham City University
- Cranfield University
- Manchester Metropolitan University
- QUEENS UNIVERSITY BELFAST
- University of Cambridge
- University of Leeds
- University of Liverpool
- University of London
- University of Manchester
- University of Salford
- University of Sheffield
- University of Stirling
- 18 more »
- « less
-
Field
-
skills and desirably some computer modelling experience, and an ability to work in a multidisciplinary team and engage confidently with partners. You will have a track record of publishing high impact
-
methods to economic and environmental problems; Knowledge of STATA, R, Python and/or other relevant programming skills for undertaking applied analysis (e.g. machine learning) and handling large
-
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
-
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
-
. 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
-
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
-
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
-
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
-
. 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
-
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