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University of Pennsylvania
Philadelphia, Pennsylvania, United States
(on-site)
Posted
28 days ago
University of Pennsylvania
Philadelphia, Pennsylvania, United States
(on-site)
Job Type
Full-Time
Job Function
Research
Postdoctoral Researcher in Bio/Statistics and Machine Learning
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Postdoctoral Researcher in Bio/Statistics and Machine Learning
The insights provided are generated by AI and may contain inaccuracies. Please independently verify any critical information before relying on it.
Description

Postdoctoral Researcher in Bio/Statistics and Machine Learning
Location: University of Pennsylvania - Perelman School of Medicine
Open Date: Sep 18, 2025
Deadline:
Faculty Mentor: Qi Long, Ph.D.
Department: Biostatistics, Epidemiology and Informatics
Funding Sources: Grant
Number of Positions: 1
Open to applications from U.S. citizens and foreign nationals.
The University of Pennsylvania, the largest private employer in Philadelphia, is a world-renowned leader in education, research, and innovation. This historic, Ivy League school consistently ranks among the top 10 universities in the annual U.S. News & World Report survey. Penn has 12 highly-regarded schools that provide opportunities for undergraduate, graduate and continuing education, all influenced by Penn's distinctive interdisciplinary approach to scholarship and learning.
Penn offers a unique working environment within the city of Philadelphia. The University is situated on a beautiful urban campus, with easy access to a range of educational, cultural, and recreational activities. With its historical significance and landmarks, lively cultural offerings, and wide variety of atmospheres, Philadelphia is the perfect place to call home for work and play.
Duties & Responsibilities: We invite applications for a post-doctoral researcher position in Dr. Qi Long's lab (https://www.med.upenn.edu/long-lab/). The position is open until filled and the initial appointment is for two years with a possible extension for a third year.
The position will offer opportunities to conduct research on 1) statistical foundations of large language models (LLMS) under joint supervision of Dr. Weijie Su (https://www.weijie-su.com/), or 2) development and assessment of foundation models and agentic AI for biomedical research and healthcare using multimodal data such as electronic health records (EHRs) data, multi-omics data and imaging data in collaboration with researchers in radiology and computer science.
Successful post-doctoral researcher is expected to develop independence in methodological research through activities including, but not limited to, writing peer-reviewed publications for research conferences and journals, giving presentations at research conferences, and assisting in grant proposal development.
The University of Pennsylvania is an EOE. Minorities/Women/Individuals with disabilities/Protected Veterans are encouraged to apply.
Salary: Competitive.
Qualifications
Ph.D. degree in statistics, computer science, or related quantitative fields required.
Additionally, the following skills are desirable: excellent training in statistics and/or machine learning; excellent programming skills in Python and possibly other programming languages such as C++ and Java; excellent writing and oral communication skills.
Application Instructions
Review of applications will begin shortly and will continue until the position is filled.
Applications should be sent through Interforlio using the link below and include:
- Cover Letter
- Curriculum vitae
- Research Statement
- Contact Information for three references
To apply, visit https://apply.interfolio.com/174189
Equal Employment Opportunity Statement
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 ID: 84301052
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