Sort by
Refine Your Search
-
Listed
-
Employer
- ;
- UNIVERSITY OF SOUTHAMPTON
- University of Birmingham
- SINGAPORE INSTITUTE OF TECHNOLOGY (SIT)
- City University London
- KINGS COLLEGE LONDON
- University of Glasgow
- University of Nottingham
- Edinburgh Napier University;
- King's College London
- Nature Careers
- The University of Southampton
- UNIVERSITY OF SURREY
- University of Bristol
- University of Sheffield
- 5 more »
- « less
-
Field
-
responsibilities Research: Contribute to or lead on the statistical aspects of the development of high quality research bids to evaluate the effectiveness of new health technologies, which is recognised both
-
for this role. This role will involve developing and applying analysis plans using a variety of advanced methods with the support of project supervisors. The postholder will have completed a PhD in a relevant
-
change to delivery of health services. Experience with large datasets and excellent communications skills will be essential for this role. This role will involve developing and applying analysis plans
-
COG-MHEAR is a world-leading cross-disciplinary research programme funded under the EPSRC Transformative Healthcare Technologies 2050 Call. The programme aims to develop truly personalized
-
bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms Downloading a copy of our Job Description Full
-
. In this role, you will be part of the research team, working to develop and evaluate privacy-preserved Generative AI algorithms for generating synthetic Personal Identity Information (PII). This aims
-
inversion techniques and signal processing. Strong programming skills, Proficiency in scientific computing (e.g. Python, MATLAB, or similar) for algorithm development and data handling. Experience with sensor
-
John Williamson, and Dr Sebastian Stein. The job requires the proven ability to develop novel theory and build and evaluate working interactive prototypes involving complex computational models
-
Experience with machine learning algorithms and ideally experience developing novel methods Understanding of basic biological principles and experience interpreting ‘omics data Ability to analyse information