Sort by
Refine Your Search
-
Listed
-
Category
-
Employer
- University of Oxford
- KINGS COLLEGE LONDON
- AALTO UNIVERSITY
- King's College London
- University of London
- UNIVERSITY OF VIENNA
- DURHAM UNIVERSITY
- University of Liverpool
- Durham University
- Heriot Watt University
- Imperial College London
- ;
- King's College London;
- The University of Edinburgh;
- University of Liverpool;
- University of Oxford;
- Imperial College London;
- University of Wolverhampton
- CZECH UNIVERSITY OF LIFE SCIENCES
- Queen Mary University of London;
- Royal College of Art;
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- University of Sheffield
- Aston University
- Atlantic Technological University;
- Birkbeck, University of London;
- Bournemouth University;
- City University London
- Durham University;
- Heriot-Watt University;
- John Innes Centre
- Northumbria University;
- Oxford Brookes University
- Royal College of Art
- Royal Holloway, University of London;
- SOAS University of London;
- Technical University of Denmark
- University of Bradford;
- University of Cambridge
- University of Cambridge;
- University of Essex;
- University of Exeter
- University of Exeter;
- University of Glasgow
- University of Glasgow;
- University of Leicester
- University of Lincoln
- University of Sheffield;
- 38 more »
- « less
-
Field
-
. Through the MRC-funded OpenEP|NET study the post-holder will work closely with the existing study team, supporting system development, technical processing, data management and data science aspects
-
groups working on digital health and wellbeing , network science , computational social science , and various topics in machine learning. You will be working in the research group of one of the PIs
-
frameworks and pipelines Familiarity with single-cell multi-omic data integration and network or pathway inference tools Experience working in high-performance computing or cloud environments Interest in
-
contact with participants after they have taken part in the research. Support the development and submission of funding bids including: working on data and impact plans, networking with non-academic
-
About the role The University of Leicester is proud to be part of the UK Nuclear Deterrence Network, a collaborative initiative with King’s College London and the Royal United Services Institute. As
-
demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
-
demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
-
provision including flexible working, caring support (including a Parenting and Carers Fund and the Carer’s Career Development Fund), training, and a variety of diversity and inclusion networks. Staff can
-
immunocytochemistry, electrophysiology and live cells imaging. The aim of the projects is to approximate cellular phenotypes in an in vitro model of Bipolar Disorder (BD), and attributing abnormal network activity
-
novel photonic techniques such as time resolved single photon technologies, spectral imaging, and optical fibre sensors to tackle clinical/biomedical challenges and other real world applications. Our work