Sort by
Refine Your Search
-
Listed
-
Employer
- ;
- University of Birmingham
- University of Nottingham
- City University London
- KINGS COLLEGE LONDON
- King's College London
- University of Cambridge
- CRANFIELD UNIVERSITY
- Cranfield University
- The University of Southampton
- UNIVERSITY OF SOUTHAMPTON
- University College London
- University of Leeds
- 3 more »
- « less
-
Field
-
Lanterna in the School of Chemistry, University of Nottingham. The project focuses on Mapping Photocatalysts using Tandem Super-resolution Electron Microscopy and Spectroscopy in collaboration with
-
mapping to join our team developing decision support systems for improved schistosomiasis control during water infrastructure projects. About the Role Schistosomiasis often spreads in areas with water
-
/2025 Role Description An exciting opportunity for an established researcher or a recently completed PhD researcher with experience in malacology, epidemiology, data mapping and/or schistosomiasis
-
to £41,478 per annum. An exciting opportunity for an established researcher or a recently completed PhD researcher with experience in malacology, epidemiology, data mapping and/or schistosomiasis modelling and
-
Medicine (CTM) (50%). This post will support analysis of multiomics data (e.g. single cell and single nuclear RNA-seq, spatial transcriptomics, proteomics etc.) generated by the Borne Uterine Mapping Project
-
modelling, satellite data assimilation, multivariate statistics, and machine learning. Prior experience with model and satellite products for mapping and understanding SM-dependent hazards (like floods
-
modelling, satellite data assimilation, multivariate statistics, and machine learning. Prior experience with model and satellite products for mapping and understanding SM-dependent hazards (like floods
-
currently exists to map and explain the diverse mechanisms of housing exclusion. Addressing this gap requires integrating geospatial analysis, explainable AI (XAI), and behavioural research methods, including
-
collaboration that has mapped emotional hotspots in four cities in the UK and EU using spatial analysis of social media data. The next phase of the project aims to incorporate explainable AI (XAI) to interpret
-
%). This post will support analysis of multiomics data (e.g. single cell and single nuclear RNA-seq, spatial transcriptomics, proteomics etc.) generated by the Borne Uterine Mapping Project (BUMP, focussed