Job Description

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The Department of Biostatistics and Epidemiology at the Perelman School of Medicine at the University of Pennsylvania seeks candidates for several Research Associate positions in the Academic Support Staff. This appointment will be initially for one (1) year and continuation during that time period and renewal are based on satisfactory performance and availability of funding (limited to three (3) years). Expertise is required in the specific area of longitudinal causal inference methods and/or the design, evaluation, and application of research methods, as well as a specific area of epidemiology, (bio)statistics, or a related field of quantitative or computational science. Applicants must have at least one year of postdoctoral experience. Applicants must have a Ph.D. or equivalent degree.

Responsibilities May Include

• Development and application of statistical, causal, and machine learning methods for analyzing complex longitudinal data structures, including electronic health records (EHRs), registry data, biobanks, pragmatic trials and cohort studies;
• Collaboration on research projects across the palliative care, critical care, and health services research spectrum, working alongside faculty in the Department and a dynamic team of clinician-scientists, epidemiologists, and biostatisticians; and
• Support for methodological development in clinical trials design, analysis, and monitoring; observational studies; and Bayesian causal inference applications.

The successful applicant will have an opportunity to work under the supervision of Dr. Michael Harhay and collaborators at the Center for Clinical Trials Innovation, with increasing autonomy to independently lead innovative methodological developments (particularly Bayesian components of funded projects) and author peer-reviewed publications. Collaborative contributions to team science are expected alongside building a clear path toward independent research in preparation for the next stage of their career.

The University of Pennsylvania is an equal opportunity employer. Candidates are considered for employment without regard to race, color, sex, sexual orientation, religion, creed, national origin (including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state, or local law.

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Job Tags

Full time, Local area,

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