[AISWorld] RESEARCH FELLOW: University of Michigan School of Information

[Lionel Robert]

RESEARCH FELLOW: University of Michigan School of Information Job Summary

The School of Information (in connection and collaboration with School of
Public Health and Urban and Regional Planning Program at the Taubman
College of Architecture and Urban Planning) are offering a postdoctoral
fellow position in the multidisciplinary area of "big data and community
health."

The burden of negative health outcomes is, unfortunately, differential in
the United States (US). Living in an area in which a large proportion of
residents are socio-economically disadvantaged exerts an independent,
negative effect on individual health status. Initiatives to reduce such
neighborhood-based health disparities, or "neighborhood effects", require
access to meaningful, timely, and actionable information regarding the
health of different groups, and factors that influence their health. Yet,
there are key gaps in the country's population health information
infrastructure, including a lack of accepted measures of community health
and the fact that many existing data are not fully exploited nor
effectively linked. In part, these gaps are due to the challenges of
gathering and analyzing large, diverse, dynamic, and relevant data sets.
The project will address these challenges by leveraging emerging "big data"
sources such as social media sites and citizen-created maps, while linking
new sources with existing health data sets.
Responsibilities*

The postdoctoral fellow will help lead the efforts to: 1) Collect, process,
and analyze geo-tagged social media data to measure neighborhood
characteristics that are related to health disparities; 2) Compare social
media measures with other existing data sets; and 3) Combine machine
learning and spatial statistical techniques to explore and model the
relationship between neighborhood characteristics and health behaviors.

This position will fund a researcher who will have the opportunity to work
alongside an interdisciplinary team of collaborators to develop "big data
and community health" as an area of research. The team of investigators
includes: Dr. Tiffany Veinot (School of Information and Department of
Health Behavior and Health Education, School of Public Health), Dr. Robert
Goodspeed (Urban and Regional Planning Program, Taubman College of
Architecture and Urban Planning), Dr. Veronica Berrocal (Department of
Biostatistics), Dr. Daniel Romero (School of Information and Department of
Computer Science, College of Engineering) and Dr. Phillipa Clarke
(Institute for Social Research). The postdoctoral fellow will be an equal
member of the interdisciplinary research group.

The postdoctoral fellow will be expected not only to conduct independent
research, but also to collaborate actively in the aforementioned research
project with faculty, graduate students, and undergraduate research
assistants. This responsibility includes regular communication and
coordination with the project team. The postdoc will also be expected to
contribute substantially to publications related to "big data and community
health," acting as first author on some and as a secondary author on others.

The postdoctoral fellow will have shared office space at the University of
Michigan and may have the opportunity to teach one course in the School (to
be negotiated with the appropriate dean).
Required Qualifications*

*A Ph.D. in a related area completed by the position start date. The ideal
candidate will have a PhD in Computer Science, Statistics, Mathematics,
Information, Geography, Public Health or a related field.
*A strong background and experience with machine learning, data mining,
and/or spatial statistic methods.
*Programming experience and comfort with handling and analyzing big data
sets.
*Motivation and initiative, excellent communication skills, and the ability
to work independently as well as in a team.
*A desire to learn and contribute to the field of Public Health is
preferred.
How to Apply

Please apply on this site by uploading just your resume.

In addition, applicants should submit the following materials
electronically to Professor Tiffany Veinot:

Email tveinot at umich.edu one PDF file which includes:
1. A statement of interest describing your relevant background and skills
2. A current curriculum vitae/resume
3. The name and contact information for three references. (One reference
should be your doctoral advisor.) Letters of recommendation will only be
solicited from finalists.
4. Two publications or other writing samples.

Review of applications will begin immediately and continue until the
position is filled.

Link: http://umjobs.org/job_detail/106604/research_fellow



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Lionel P. Robert Jr.
Assistant Professor of Information
School of Information
University of Michigan
4381 North Quad
Ann Arbor, MI 48109-1285
Phone: 734-764-5296
Fax: 734-615-3587
Email: lprobert at umich.edu
https://www.si.umich.edu/people/lionel-robert
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