Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oxford
- KINGS COLLEGE LONDON
- University of Oxford;
- UNIVERSITY OF VIENNA
- University of London
- King's College London
- AALTO UNIVERSITY
- Imperial College London
- Durham University
- University of Cambridge;
- jobs.ac.uk
- ;
- DURHAM UNIVERSITY
- Heriot Watt University
- Imperial College London;
- King's College London;
- Manchester Metropolitan University
- Nature Careers
- Northumbria University;
- Oxford Brookes University;
- Queen Mary University of London;
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- The University of Edinburgh;
- University of Bradford;
- University of Dundee;
- University of Exeter
- University of Exeter;
- University of Glasgow
- University of Greenwich
- University of Greenwich;
- University of Kent;
- University of Liverpool
- University of Newcastle
- University of Nottingham
- University of Reading
- 25 more »
- « less
-
Field
-
. About the Role The post is funded for 3 years and is based in the Big Data Institute, Old Road Campus. You will join an interdisciplinary team of researchers spanning imaging science, machine learning
-
foundational theory of how large ML systems can be regularised to have dramatically fewer trainable parameters without sacrificing accuracy by analysing the use of low-dimensional building blocks Implicit
-
of therapeutic genomics, leveraging large-scale functional genomic datasets and cutting-edge computational resources, including university HPC clusters and AWS. The post-holder will advise colleagues on data
-
You will have or be close to the completion of a PhD/DPhil in epidemiology, biostatistics or big data, along with demonstrable experience of working with population registers and large datasets. With
-
between the two linked studies as well as taking the lead in the large-scale qualitative secondary analysis of interview data from multiple sources. In this role you will be expected to contribute
-
equivalent to PhD level in health data science or similar field. Experience working within multidisciplinary teams, in medical statistics and in the analysis of large healthcare datasets (such as CPRD
-
be close to the completion of a PhD/DPhil in epidemiology, biostatistics or big data, along with demonstrable experience of working with population registers and large datasets. With proven
-
language processing, historical linguistics, and computational humanities. The postholder will lead the computational stream of the project, which involves building a large corpus of Latin texts (data collection and
-
with the possibility of renewal. This project addresses the high computational and energy costs of Large Language Models (LLMs) by developing more efficient training and inference methods, particularly
-
qualification/experience equivalent to PhD level in health data science or similar field. Experience working within multidisciplinary teams and in the preparation and analysis of large healthcare datasets such as