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Postdoctoral Research Fellow Position: Social Determinants of Health and Racial Disparities in Cancer
Open Date: December 12, 2023
Description:
The Health Equity Data Lab (HEDL) at the Lucy Family Institute for Data and Society (LFIDS) seeks highly motivated and enthusiastic candidates for a Resident Scholar Postdoctoral Fellow in the area of racial disparities and social determinants of health in cancer incidence and outcomes. This exciting interdisciplinary project lies at the convergence of network science and bioinformatics, and is led and managed by two PIs who are experts in their respective fields: Prof. Meenal Datta in the College of Engineering (cancer biology) and Prof. Margaret Traeger in the Mendoza College of Business (network science). This institute-supported project centers around collection and evaluation of social, health, and biological data to identify actionable paths forward to reduce cancer burden and improve survivorship in the nation’s most vulnerable communities.
Qualifications:
Successful candidate must have the following qualifications:
- PhD or equivalent in Network Science, Data Science, Bioinformatics, Sociology, Biology, or a similar field.
- Experience in robust data science techniques (e.g., with R, Python)
Additional Qualifications:
- Candidates with expertise in social determinants of health and/or racial disparities in human health and disease will be viewed favorably.
- Experience in machine learning and/or multi-modal data integration is desirable.
- Women, minorities, and members of other underrepresented groups are especially encouraged to apply.
Application Instructions:
Applicants should send a brief description of their research interests, a curriculum vitae, anticipated start dates, and the names of at least three references via Intefolio Dossier.
Postdoctoral Research Fellow Position: Health Equity Data Lab
Open Date: October 16, 2023
Description:
The Health Equity Data Lab (HEDL) at the Lucy Family Institute for Data and Society (LFIDS) seeks highly motivated and enthusiastic candidates to fill a post-doctoral fellow position at the intersection of data and health-related topics. Of special interest to this position are topics of sexual and reproductive health measure development, maternal health measure development, health-related comparative studies, or related subjects. The post-doctoral fellow with work with Dr. Sarah Mustillo and Dr. Nitesh Chawla, as well as other faculty and staff at the HEDL and industry partners from multiple major organizations in the health care field. This fellowship presents unique opportunities for post-doctoral researchers to gain research experience, and professional development, and work on a national project with a dynamic interdisciplinary team.
Qualifications:
Open to applicants from any relevant discipline, including but not limited to social and behavioral sciences (e.g., sociology, psychology, public health, political science).
- Must have received a doctoral degree from an accredited educational institution by the start of appointment.
- Strong interest and research experience in quantitative methodology required including data management (merging datasets, recoding variables, cleaning data), and data analysis (categorical data analysis and regression), and experience managing research projects.
- Interest and experience in qualitative methodology, including conducting interviews and analyzing interview data, is a plus.
- Experience in any of the following areas is desirable: machine learning, multi-modal data integration, imbalanced learning, and responsible AI topics.
- Excellent oral and written communication skills are essential.
- Strong interpersonal and organizational skills are required.
- Demonstrated successful dissemination of scholarship would be an advantage.
- Women, minorities, and members of other underrepresented groups are especially encouraged to apply.
Application Instructions:
Applicants should send a brief description of their research interests, a curriculum vitae, anticipated start dates, and three confidential letters of recommendation via Intefolio Dossier.