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Associate Professor of Statistics and Data Science (Tenure-Track) 2026 - 2027

University of Pennsylvania

Philadelphia, PAFull-timeSeen 2w agoSeen in employer's feed 1w ago

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At a glance

Compensation
No compensation found
Location
Philadelphia, PA
Schedule
Full-time
Work Authorization
Not specified

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Requirements

Credentials this posting asks for.

Doctorate

Job overview

The Department of Statistics and Data Science of the Wharton School, University of Pennsylvania, is seeking applicants for a full-time, tenure‑track Associate Professor position beginning July 1, 2027. Candidates must demonstrate outstanding research capacity, achievement, and excellent teaching and communication skills, and hold a Ph.D. or equivalent.

Skills & qualifications

RequiredNice to have

Skills

ResearchTeachingCommunication

Qualifications

Ph.D. Or Equivalent

Full job description

The Department of Statistics and Data Science of the Wharton School, University of Pennsylvania, is seeking applicants for a full-time, tenure-track Associate Professor position. The appointment is expected to begin July 1, 2027.

Applicants must show outstanding capacity and achievement in research, as well as excellent teaching and communication skills. Applicants must have a Ph.D. or equivalent from an accredited institution.

To apply, please submit the following materials through our online application system:

  • Cover letter.

  • Curriculum vitae.

  • Statements on research and teaching.

  • Up to 3 selected publications or preprints if available (optional).

For full consideration, candidates are encouraged to have all required application documents submitted by November 15, 2026.

Any questions can be sent to [email protected].

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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