Postdoctoral Associate - Complexity Science and Data Analytics

Reference: IRG_FM_2017_012
Date Posted: 23 February 2017
Group: Future Urban Mobility

Project OverviewSingapore-MIT Alliance for Research and Technology (SMART) is looking for an exceptional candidate to join MIT Senseable City Lab in Singapore and to fill a Postdoctoral Assoicate position for the modeling and analysis of complex urban systems through big data created by human activity.

Since its inception, the Lab has acquired massive and unique data sets about different aspects of human behavior in cities all over the world and together with its partners – world leading industrial companies and organizations – has launched a major interdisciplinary initiative to harness these unprecedented data sets in order to better understand cities as 'complex systems', being able to model their dynamics and create innovative solutions for improving urban life.

Responsibilities

• Analyze big datasets created by human activity.
• Perform fundamental and applied research on quantifying, modeling and predicting human behavior within urban environment including mobility, social interactions, and economic activity.
• Evaluate uses of urban big data for characterizing social aspects of modern urban environments including segregation and inclusion, and possible ways for quantifying the effects of new "smart" technologies.
• Work in collaboration with the lab’s multidisciplinary team, external research and industrial partners.
• Actively contribute to the design and initiation of new research projects and ideas in the field of complex urban systems, in the intersection of computer science, network science, social sciences and urban planning.
• Participate in the applied projects with lab’s industrial partners.
• Present research results at top international workshops and conferences, exhibits as well as internal project meetings.
• Co-author articles for publication in top-tier peer-reviewed journals and top conferences.

RequirementsThe successful candidates must hold a doctoral degree in Mathematics, Physics, Complex Systems or a related field. Candidates with an interdisciplinary mathematical modeling background are also given particular attention. Ability of working in a multidisciplinary team environment, problem solving skills and high creativity are very welcome.

• Formal or informal education in machine learning and statistics is required.
• Practical skills in Matlab and Python are expected.
• Experience in human mobility and/or social network analysis is a strong plus.
• C++, Java, Hadoop, MapReduce and other relevant technologies are a plus.
• Demonstrated record of independent thinking and innovative scientific accomplishments as evidenced by first-author papers published in premier journals is a strong plus.
• Outstanding oral and written communication skills in English as evidenced by ability to develop manuscripts and deliver presentations are required.

Interested applicants will have to submit their full CV/resume, cover letter and list of three references (to include reference names and contact information). We regret that only shortlisted candidates will be notified.

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