Application Period: April 11, 2019 - May 11, 2019
Contact: Professors C Barrington-Leigh or J Baumgartner at McGill
This is an exciting opportunity for a highly-motivated computer scientist to join a dynamic research consortium and contribute to innovative research through the application of computer vision and deep learning techniques to street and satellite imagery from diverse global cities to further a global environment and health agenda. The position can be tailored into a Postdoctoral Fellowship or a Research Staff depending on the applicant.
The research involves a consortium of leading universities as well as policy agencies throughout the world, and is highly interdisciplinary (equitablehealthycities.org/partners). We plan to use methods and tools from a range of disciplines to model the impacts of policy scenarios on the environment and health in cities in high- and low-income countries. We have a particular focus on using emerging data and novel methods to characterise cities’ environment and health, with emphasis on within-city variations and inequalities. The person appointed to this important post will have a key role in identifying and implementing the consortium’s data and analytical strategy for using multiple street-level and satellite imagery sources to build new datasets that complement existing administrative and other authoritative data.
The position will be based at McGill’s Institute for Health and Social Policy and work closely with researchers in several departments at McGill, as well as at our partner institutions, including Imperial College London, University of Chicago and the University of Ghana. The group is highly interdisciplinary and the post holder will work closely with a range of backgrounds and disciplines in an international group based at McGill and at other leading global universities. The successful Research Associate or Postdoc will benefit from opportunities to collaborate with world-class investigators in Canada and abroad, attend technical workshops and yearly international team meetings, and participate in domestic and international research exchanges.
Candidates must have an exceptional aptitude for analytical and critical thinking about scientific problems, data, and analytical methods; superb programming skills; strong communication capabilities; motivation for problem solving; aptitude for interdisciplinary research and teamwork; and ability to work and learn independently. For postdoctoral appointees, there will be scope for the post holder to transition from mentored research to an independent research agenda.
Additional duties for postdoctoral appointees
Application details: Interested candidates should email firstname.lastname@example.org (with subject: Image Machine Learning Position) with a single PDF containing (in order):
Review of applications will begin immediately. Shortlisted candidates will be contacted. We welcome applications from indigenous peoples, visible minorities, ethnic minorities, persons with disabilities, women, persons of minority sexual orientations and gender identities, and others who may contribute to further diversification.