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Postoctoral Researcher
Postoctoral ResearcherInsideHigherEd • Philadelphia, Pennsylvania, United States
Postoctoral Researcher

Postoctoral Researcher

InsideHigherEd • Philadelphia, Pennsylvania, United States
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  • [job_card.full_time]
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Postoctoral Researcher


Location: University of Pennsylvania - School of Medicine
Open Date: Oct 09, 2025
Deadline:

Faculty Mentor: Samantha Piekos, 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 and Responsibilities
  • Integrate and analyze longitudinal multi-omics datasets (lipidomics, metabolomics, proteomics, transcriptomics) from blood, urine, and placenta with vaginal and gut microbiome, wearable, clinical and environmental data.
  • Perform network analyses, including community structure modeling, to characterize physiological changes across pregnancy.
  • Identify molecular disruptions in obstetric syndromes (e.g., preeclampsia, gestational hypertension, preterm birth).
  • Apply trajectory modeling and outlier detection to identify earliest deviations from healthy pregnancy pathways.
  • Collaborate with clinical and experimental teams to generate biologically meaningful insights.
  • Develop independence 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 position is open until filled. The initial appointment is for two years, with the possibility of extension for a third year based on performance and mutual agreement.

The University of Pennsylvania is an EOE. Minorities/Women/Individuals with disabilities/Protected Veterans are encouraged to apply.



Qualifications

  • Required Qualifications
  • Ph.D. in Bioinformatics, Computational Biology, Computer Science, Systems Biology, Statistics, or a related field.
  • Demonstrated expertise in data integration, machine learning, or network biology.
  • Experience with large-scale omics data analysis.
  • Proficiency in R and/or Python programming.
  • Strong statistical and modeling skills.
  • Excellent communication and writing abilities.



Preferred Qualifications
  • Experience in multi-omics integration frameworks and dimensionality reduction.
  • Familiarity with longitudinal or epidemiological study design.
  • Background in systems biology of complex physiological processes.
  • Knowledge of AI/ML methods for trajectory prediction and anomaly detection.
  • Interest in maternal-fetal health, developmental biology, or reproductive biology.


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 (2-pages)
  • Contact Information for three references




To apply, visit https://apply.interfolio.com/175355

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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