Job Details

Position Number: 7112104
Location: Philadelphia, PA
Position Type: Medicine - Medical Researcher

Postdoctoral Researchers - bench and dry lab scientists in the field of lipoprotein metabolism and the role of lipids in cardiometabolic traits and diseases (including atherosclerosis and metabolic dysfunction-associated steatotic liver disease or MASLD)

Location: University of Pennsylvania - Perelman School of Medicine
Open Date: Apr 17, 2026
Deadline:

Faculty Mentor: Daniel J. Rader MD
Hiring Department: Medicine - Division of Translational Medicine and Human Genetics
Funding Sources: NIH and AHA grants
Number of Positions: 2
U.S. citizens and foreign nationals may apply.

Applications are invited for postdoctoral positions in the laboratory of Dr. Daniel J. Rader, Departments of Medicine and Genetics at the Perelman School of Medicine (PSOM) of the University of Pennsylvania. The Rader lab is a multidisciplinary research environment focused on leveraging human gene discovery to elucidate the biology and molecular physiology of genes and pathways that influence plasma lipoprotein metabolism as well as the role of lipids in cardiometabolic traits and diseases (including atherosclerosis and metabolic dysfunction-associated steatotic liver disease or MASLD) and neurodegeneration/Alzheimer's disease. The lab integrates computational genomics, fundamental molecular investigation in cell and animal model systems, and targeted deep phenotyping in human subjects to establish molecular mechanisms, clinical relevance and accelerate translation of research insights to potential treatment of human cardiometabolic disorders. Approaches to this work incorporate 1) computational multi-omics to identify genes and pathways of interest; 2) human induced pluripotent stem cell (iPSC)-derived cell types to examine impact on hallmarks or biomarkers of phenotype and/or disease; 3) mouse model systems including germline and somatic gene manipulation; 4) use of natural genetic variants to elucidate protein structure-function relationships, and 5) recall-by-genotype studies in humans for deep phenotyping to inform genotype-phenotype relationships. We particularly encourage inquiries from 1) bench scientists with some background in lipid metabolism and 2) dry lab scientists with experience in bioinformatics and high-throughput genomics, metabolomics and/or proteomics technologies.

Qualifications
Bench scientists: PhD in a biological science and a strong record of academic productivity are required; excellent written and verbal communication skills are also required. Individuals should be able to demonstrate an ability to successfully complete projects independently. Applicants with experience in genetics/genomics, biochemistry, cell biology, or physiology, and/or cell and mouse models, are encouraged to apply. We are particularly interested in bench scientists with some background in lipid metabolism.

Dry lab scientists: Ph.D. degree in Biostatistics, Computer Science, Bioinformatics, or other biomedical domain required. A strong record of academic productivity, excellent written and verbal communication skills are also required. Individuals should be able to demonstrate an ability to successfully complete projects independently. Additionally, the following skills are desirable: fluency in statistical and data management computer languages such as R, Python, Bash, and SQL. We are particularly interested in individuals with experience in bioinformatics and high-throughput genomics, metabolomics and/or proteomics technologies.

Application Instructions
To apply, please submit the following through Interfolio:

1. Brief statement of your research experience and interests detailing your qualifications for this position

2. Curriculum Vitae

3. Name and contact information of three references.

To apply, visit https://apply.interfolio.com/184733

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.