Urban Data Science is where city and urban data are used with AI and machine learning methods to tackle the most complex socio-economical challenges: equity, climate resilience, and quality of life.
The candidate will develop theoretical questions and models towards helping cities become climate-neutral in 2030, for example through transition to sustainable transportation modes. The candidate will collaborate with city officials in urban intervention projects, as well as with the rest of the team and group researchers.
The candidate will prepare and analyse geolocated data from multiple heterogeneous sources, and create models that use these data to answer questions posed by the researchers as well as administration officials and other collaborators.
The candidate will be embedded in the Data Analytics and Visualization Group, within the Computational Applications in Science and Engineering department (CASE); which works with industry and academia developing software and applications that leverage the power of High-Performance Computing to solve real problems of people.
Key Duties
- Receive, ingest, prepare, and clean data from the project stakeholders
- Analyze the data and develop statistical models with focus on spatial features
- Design and implement part of the web platform that will serve urban policymakers in the cities involved in the research projects
- Aid with the synthesis, lessons for policy and planning, and dissemination activities
- Take a lead role in preparing publications and research outputs, including co-authored academic articles, policy briefs, and community events
Closing Date: Tuesday, 01 October, 2024
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