Biostatistics – Associate or Full Professor, Tenure Track or Clinician-Educator in Causal Inference

About the role

The Department of Biostatistics, Epidemiology and Informatics (DBEI) at the Perelman School of Medicine at the University of Pennsylvania seeks candidates for several Associate or Full Professor positions in either the non-tenure clinician educator track or the tenure track. Expertise is required in the specific area of causal inference methods development and applications, with the ability to establish oneself as a research leader in their area of specialization.

The placement of Biostatistics in the Perelman School of Medicine provides a rich mix of ongoing biomedical research programs and a vibrant team‑science‑oriented environment with elite biomedical research collaborators. The Division of Biostatistics includes over 30 full‑time faculty with diverse expertise, and the school hosts strong, highly ranked, and growing MS and PhD programs. This setting, together with proximity to the Wharton School, School of Arts and Sciences, School of Engineering and Applied Science, and institutions such as the Children’s Hospital of Philadelphia, offers ideal opportunities for cross‑disciplinary collaboration and impactful quantitative research.

Responsibilities

• Participate in biostatistics PhD and MS training programs.
• Teach biostatistics courses in epidemiology, health policy, and other biomedical programs.
• Demonstrate a strong commitment to teaching and mentoring.
• Develop innovative leading‑edge statistical methodology.
• Engage in collaborative research projects within the Perelman School of Medicine.
• For tenure‑track applicants: focus primarily on methodology development with secondary emphasis on collaborative research.
• For clinician‑educator track applicants: maintain outstanding productivity in collaborative research and contribute some methodological research.

Requirements / Qualifications

• Ph.D. or equivalent degree.
• Expertise in causal inference methods development and applications.
• Ability to establish oneself as a research leader in the area of specialization.
• Established track record in the development of innovative leading‑edge statistical methodology.
• Experience serving as Principal Investigator of methodological research supported by extramural grant funding.