We are looking for highly motivated and talented researchers to join our interdisciplinary team working on advanced modelling of complex large-scale urban systems, with a particular focus on land use, transport, and the built environment.
This role will involve developing, applying, and refining computational models to better understand urban dynamics, including how land use and transportation interact with the physical, social, and economic environment.
They will work with a collaborative and interdisciplinary team of scientists and engineers that have a passion in understanding the dynamics of large-scale socio-technical systems such as urban transportation (either land, air and/or sea) as well as the relationship between the built environment and social outcomes (such as health or behavioural outcomes across different population segments).
Shortlisted candidates would have the opportunity to work with various external collaborators, either from government and/or industry and work on high-impact real-world research problems, in which they will apply various computational tools such as modelling and simulation and AI to derive insights that can inform urban policy and planning.
Requirements
• Ph.D in Physics, Engineering, Data Science, Geography, or related fields
• Proficiency in Python or R with experience in geospatial and/or statistical packages
• Relevant research/project experience in either of these fields:
o Spatial analysis / Geospatial information system (GIS)
o Transportation and urban systems
o Agent-based modelling / network analysis
• Demonstrated experience in applying geospatial and/or statistical analysis or other relevant analytics tools on real urban problems would be highly desirable
• Experience working on large scale real-world datasets as well as knowledge of social dimension in urban planning would also be a plus
• Good written and verbal communication skills
• Ability to work effectively in an interdisciplinary research environment both individually as well as in a team, with a strong interest in collaborative research and policy impact
