24mth Geospatial Data Post-doc Available
This exciting position will allow the successful candidate to work on an international project exploring how a variety of environmental exposures over the life-course shape health outcomes, including Alzheimer’s Disease.
2 year Geospatial Data Postdoc researcher position as part of international NIH project with the Gateway for Global Ageing Data:
The School of Medicine, Dentistry & Biomedical Sciences (MDBS) at Queen’s University Belfast, is currently seeking to appoint an exceptional candidate to the post of Research Fellow within the Centre for Public Health. This exciting position will allow the successful candidate to work on an international project exploring how a variety of environmental exposures over the life-course shape health outcomes, including Alzheimer’s Disease. This project particularly focuses on air pollution, temperature, light pollution and green/blue spaces, and derivation of environmental exposure variables from vertical aerial and satellite imagery data.
To advance this agenda, we aim to expand our characterisation of the exposome by compiling additional environmental data from open-sources, vertical aerial and satellite imagery data, and to link them to survey data from eight countries, including Northern Ireland, the U.S., England, Ireland, Mexico, Chile, Dominican Republic, and India.
The post will work with other researchers in the Centre for GIS and Geomatics and School of Electronics, Electrical Engineering and Computer Science, as well as the team of international researchers working on the project.
The successful candidate must have, and your application should clearly demonstrate you have:
- Obtained or be about to obtain a PhD in environmental epidemiology, public health, geography, urban planning or related research area
- 3 years’ relevant experience and knowledge in Geographical Information Science (GIS) and the use of ESRI ArcGIS Pro and/or open source QGIS
- Experience working with vertical aerial and satellite imagery data
- Experience of R, ArcPy or Python programming languages
- Recent relevant experience applying statistical analysis techniques (e.g. regression models, Bayesian approaches) to environmental exposure data
- Relevant experience in the integration of large spatial databases
- Experience of working with public health data and environmental databases.