82 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" "U.S" "U.S" "UCL" positions at UNIVERSITY OF SOUTHAMPTON in United Kingdom
Sort by
Refine Your Search
-
Listed
-
Category
-
Field
-
information on the group and BRC: https://www.southampton.ac.uk/medicine/about/staff/hmha.page and https://www.uhs.nhs.uk/ClinicalResearchinSouthampton/Research/Facilities/NIHR-Southampton-Biomedical-Research
-
for a Data Scientist to provide expertise to help drive the development of the University’s portfolio of programmes, including leading on market viability assessments and data analysis to support this
-
About the role We are seeking an organised, detail‑oriented Clinical Research Data Integration Coordinator to work within the Cancer B‑cell Group on the CRUK Accelerator Programme “Early Cancer
-
, please contact Prof Xize Niu (email: x.niu@soton.ac.uk ). Where to apply Website https://www.timeshighereducation.com/unijobs/listing/409766/research-fellow-in-… Requirements Additional Information Work
-
on or before 2 August 2016. Where to apply Website https://www.timeshighereducation.com/unijobs/listing/409765/paediatric-asthma-a… Requirements Additional Information Work Location(s) Number of offers
-
(m.kalkowski@soton.ac.uk ) Where to apply Website https://www.timeshighereducation.com/unijobs/listing/409452/research-fellow-in-… Requirements Additional Information Work Location(s) Number of offers
-
7 Apr 2026 Job Information Organisation/Company UNIVERSITY OF SOUTHAMPTON Research Field Computer science Engineering Mathematics Physics Researcher Profile Recognised Researcher (R2) First Stage
-
in this way. For more information about this, your rights, and our approach to Data Protection and Privacy, please visit our website https://perrettlaver.com/privacy-statement/ . Please visit
-
. Where to apply Website https://www.timeshighereducation.com/unijobs/listing/408705/research-fellow-cli… Requirements Additional Information Work Location(s) Number of offers available1Company
-
, including hybrid physics-informed approaches, to improve the estimation, monitoring and prediction of hydrological variables. Big data integration: Process and fuse multi-terabyte datasets, including