Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- UNIVERSITY OF SOUTHAMPTON
- University of Birmingham
- Nature Careers
- UCL;
- KINGS COLLEGE LONDON
- University of Nottingham
- Imperial College London
- King's College London
- Plymouth University
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- UNIVERSITY OF SURREY
- ;
- Queen's University Belfast
- Queen's University Belfast;
- The University of Southampton
- University of Bath;
- University of Leeds;
- University of Oxford
- University of Plymouth;
- University of Southampton;
- ; University of Oxford
- CRANFIELD UNIVERSITY
- Cranfield University
- Cranfield University;
- EMBL-EBI - European Bioinformatics Institute
- Technical University of Denmark
- The University of Edinburgh;
- University of Exeter
- University of Glasgow
- University of Hertfordshire;
- University of Leeds
- University of London
- University of Manchester
- University of Stirling
- University of Stirling;
- 25 more »
- « less
-
Field
-
Partnership between UCL and AstraZeneca and to work as part of a cross-disciplinary team across both sites (London and Cambridge). This post is focused on the use of machine learning models of protein
-
to the project’s scope, such as mechanistic interpretability of LLMs, robustness verification of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research
-
verification of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research independence, the capacity to support junior team members, and strong communication
-
to the project’s scope, such as mechanistic interpretability of LLMs, robustness verification of machine learning models, and conformal inference. Applicants should demonstrate scientific creativity, research
-
. Coordinate modelling activities across multiple projects and deliver high-quality outputs on time. Integrate new methodologies, including AI and machine-learning approaches, into simulation design. Conduct
-
bring expertise in computational methods (such as machine learning, chemo-informatics, molecular dynamics simulation, structural biology) and / or experimental methods (such as biophysical analysis
-
large, highly diverse and multi-modal datasets (e.g., images, surveys, statistical and sensor data). Familiarity with geostatistical, GDAL, Python, PostGIS/PostgresSQL, Machine Learning, AI, Internet
-
not yet competitive for 5-year clinician scientist fellowships. This post is designed for applicants with a research interest in machine learning or data science approaches for patient stratification
-
of subsurface processes. You will be responsible for leading the development of the approach, which could include transferring learning from other geographic regions and data types, machine learning methods
-
in securing research funding is essential, as is demonstrable expertise in complex modelling techniques such as machine learning, network neuroscience, or related computational approaches. You will