Find jobs, field experiences, and internships in the public health field
Apply for this job by 02/20/2019
Employer: University of North Carolina at Chapel Hill
Located in: Chapel Hill, North Carolina
Degree Required: Bachelors
This new position is needed for multiple research studies in the Department of Urology in conjunction with the UNC Lineberger Comprehensive Cancer Center. The primary purpose of this position is the management and analysis of primary health outcomes data and large secondary healthcare databases. This position will assist with the design, analysis and interpretation of diverse health services research studies, primarily using SAS and STATA. Together with UNC Urology faculty, this person will interface directly with clinical and research partners in the UNC Lineberger Comprehensive Cancer Center to help operationalize research questions, recommend and apply analytic approaches and assist with interpretation.
Completion of a Master’s in biostatistics, epidemiology, health services research, systems engineering, or related Public Health degree is preferred OR Bachelor’s degree and at least five years working in health services or outcomes research required.
Qualifications and Experience
Demonstrated knowledge of and experience in methods appropriate for analysis of health and health outcomes. Demonstrated skill and experience with advanced SAS or STATA programming. Candidates with no previous SAS or STATA experience in the submitted application materials will not be considered. Strong skills in biostatistics and epidemiologic methods including survival analysis, longitudinal data analysis, multi-level modeling, time-varying covariates and familiarity with pharmacoepidemiologic methods (propensity score analysis, instrumental variables), Bayesian models, missing data, bootstrapping, censoring/truncation. Expertise in documenting research decisions, assumptions, and steps applied in study analysis. A history of good communication and collaborative/interpersonal skills, and proactive team orientation.
Strongly preferred: Experience in cancer research and with analysis of registry, clinical trials and administrative claims data (e.g., Medicare); and management of large, linked datasets (e.g., 250,000+ observations; 1000+ variables).
Preferred: Experience with structural equation models, joinpoint regression, cost-effectiveness analysis, machine learning, microsimulation, and other statistical packages (e.g., R, SQL, treeage). Experience with survey data, patient-reported outcomes, or coded qualitative data.
Posted on 01/18/2019
The education abroad opportunities posted on this website are not formally affiliated with the University of Minnesota and have not been fully vetted. Opportunities posted on this website should not be construed as an endorsement by the University. Please contact the Learning Abroad Center for information regarding participation on all education abroad programs.