PI: Blair Edwards
Group: Enabling Tech (Data Technologies)
Internship Cycle: Summer (June to August 2020)
Application Reference Number: BE022020DT
The factors that influence people’s health and wellbeing are complex and varied. The study of personal and clinical factors is a well-established area, but the integration of a wide range of urban, environmental and socio-demographic factors at scale has not been realised. We are looking to collaborate with academic researchers to integrate data from geospatial sources (such as land use, air quality, distance to roads, green space, location of amenities, UK census) with clinical datasets, enabling the application of machine learning techniques to explore and determine the significance of different factors.
During this project, we will explore potential datasets, store them in the IBM PAIRS Geoscope geospatial database, apply machine learning to discover different significant factors and (if time allows) develop a dashboard to display and explore the results.
- Python — at least to a basic level, including pandas and numpy (required)
- Geospatial data — some understanding of geospatial concepts
- Machine learning — some knowledge of basic techniques and concepts
Please submit your application in the form of a CV and cover letter to DLinternship.firstname.lastname@example.org.