Biostatistics Professor: Causal Inference & Methods

University of Pennsylvania

Philadelphia (Philadelphia County)

On-site

USD 90,000 - 130,000

Full time

14 days+

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Job summary

The University of Pennsylvania is seeking an Associate or Full Professor in Biostatistics for the Perelman School of Medicine. This position emphasizes causal inference methods and teaching responsibilities, alongside innovative research.

Applicants must demonstrate expertise in statistical methodology, a commitment to academic excellence, and a strong research background. Candidates will engage in collaborative projects and play a key role in training future leaders in biostatistics.

For inquiries, please contact Cathy Vallejo at vallejo@pennmedicine.upenn.edu. The role offers a vibrant research environment and strong interdisciplinary collaboration.

Qualifications

  • Required to have expertise in causal inference methods development and applications.
  • Demonstrated ability to establish oneself as a research leader.
  • Strong commitment to teaching and mentoring students.

Responsibilities

  • Develop innovative statistical methodologies.
  • Participate in biostatistics PhD and MS training programs.
  • Engage in collaborative research projects within the Perelman School of Medicine.

Skills

Expertise in causal inference methods
Research leadership
Teaching commitment

Education

Ph.D. or equivalent degree

Job description

The University of Pennsylvania is seeking an Associate or Full Professor in Biostatistics for the Perelman School of Medicine. This position emphasizes causal inference methods and teaching responsibilities, alongside innovative research.

Applicants must demonstrate expertise in statistical methodology, a commitment to academic excellence, and a strong research background. Candidates will engage in collaborative projects and play a key role in training future leaders in biostatistics.

For inquiries, please contact Cathy Vallejo at vallejo@pennmedicine.upenn.edu. The role offers a vibrant research environment and strong interdisciplinary collaboration.

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