Research Fellow

Location
Michigan, United States
Posted
08 Feb 2019
End of advertisement period
08 Mar 2019
Ref
167943
Academic Discipline
Life sciences, Biological Sciences
Contract Type
Permanent
Hours
Full Time

All applications are accepted via the University of Michigan applicant management system by attaching one PDF file. The applicant management system website is http://careers.umich.edu/. Use keyword search to find job number 167943. Applications should submit a cover letter including a statement of career goals (one paragraph), CV, sample research papers, and names and complete contact information for at least three references.

Applications will be reviewed as received, and it is anticipated that the short-listed finalists for the position will be interviewed on a rolling basis.

Job Summary

The BioSocial Methods Collaborative, directed by Dr. Richard Gonzalez, Amos N. Tversky Professor of Psychology and Statistics, is a research methods hub located at the University of Michigan within the Institute for Social Research (ISR), has an opening for a post-doctoral research fellow. The researcher will assist with analytic and modeling efforts of existing data sets that include multiple biological and behavioral variables as well as the design of new data collection efforts. The goal of the center is to develop new modeling approaches for the integration of biological, social, behavioral and psychological variables. Duties and responsibilities include, but are not limited to: model data and interpret results; literature reviews; investigate, develop, apply, and validate new method in support of research objectives; write scientific manuscripts; present results at national conferences; provide support for grant writing; and provide technical expertise for analysis of biopsychosocial data and development of new analytic methods.

Required Qualifications*

Ph.D. in a social science field such as Psychology or quantitative field such as Statistics, with a record of peer-reviewed publications is required. Extensive experience with multiple statistical software and programming languages is required (R, Mplus, Matlab, Python, SAS, Stata, etc). Demonstrated ability to develop and implement new quantitative approaches. Ability to work independently on designated projects. Ability to work in a multidisciplinary team environment. Demonstrated interpersonal skills and oral/written communication are necessary.

Desired Qualifications*

Experience with NIH grant writing and submission preferred. Experience with biologically-based data (brain imaging data, hormonal data, physiological data, genetic data, etc.) is preferred.

Additional Information

This job posting will be posted for a minimum of fourteen calendar days.   This job may be removed from posting boards and filled any time after the minimum period has ended.  

The position begins in the summer of 2019 and is a TWO YEAR TERM LIMITED APPOINTMENT, with renewal contingent on availability of funds, satisfactory performance, acceptable progress in carrying out the assigned duties, and mutual agreement. This is a 100% appointment. Salary is commensurate with experience.

Background Screening: The University of Michigan conducts background checks on all job candidates upon acceptance of a contingent offer and may use a third-party administrator to conduct background checks. Background checks will be performed in compliance with the Fair Credit Reporting Act.

Questions about the position can be directed to: Jeannette Jackson, Managing Director of the BioSocial Methods Collaborative located at the Institute for Social Research, University of Michigan Email: jackjean@umich.edu BioSocial Methods Collaborative website: https://biosocialmethods.isr.umich.edu/.umich.edu

The Institute for Social Research at the University of Michigan seeks to recruit and retain a diverse workforce as a reflection of our commitment to serve the diverse people of Michigan, to maintain the excellence of the university, and to ground our research in varied disciplines, perspectives, and ways of knowing and learning.

U-M EEO/AA Statement

The University of Michigan is an equal opportunity/affirmative action employer.