The University of Michigan
announces a one-year postdoctoral fellowship position. The position will start
May 1, 2015.
Salary: $50,000 per year, plus a competitive benefits package and the opportunity to appoint and supervise one or more paid undergraduate research assistants to work on projects of your choice.
To applySalary: $50,000 per year, plus a competitive benefits package and the opportunity to appoint and supervise one or more paid undergraduate research assistants to work on projects of your choice.
Candidates should submit the following materials electronically to Prof. Tiffany Veinot at
Email tveinot@umich.edu one PDF file which includes
1. A statement of
interest describing your relevant background and skill
2. A current
curriculum vitae
3. The name and contact
information for three references. (One reference should be your doctoral
advisor.)
4. Letters of recommendation
will only be solicited from finalists
5. Two publications
or other writing samples
Review of applications will
begin immediately and continue until the position is filled.
Position Description
The School of Information, School of Public Health and Urban and Regional Planning Program (at the Taubman College of Architecture and Urban Planning) are jointly 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.
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 office space at the University of Michigan and may have the opportunity to
teach one course in the School (to be negotiated).
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, Public Health, Geography 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.
Non-Discrimination Policy Notice
The University of Michigan, as an equal
opportunity/affirmative action employer, complies with all applicable federal
and state laws regarding nondiscrimination and affirmative action. The
University of Michigan is committed to a policy of equal opportunity for all
persons and does not discriminate on the basis of race, color, national origin,
age, marital status, sex, sexual orientation, gender identity, gender
expression, disability, religion, height, weight, or veteran status in
employment, educational programs and activities, and admissions. Inquiries or
complaints may be addressed to the Senior Director for Institutional Equity,
and Title IX/Section 504/ADA Coordinator, Office of Institutional Equity, 2072
Administrative Services Building, Ann Arbor, Michigan 48109-1432, 734-763-0235, TTY 734-647-1388. For other University of Michigan information call 734-764-1817.
Application deadline: February 28, 2015
For more information, contact: Tiffany
Veinot, tveinot@umich.edu
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