Summary
The Zhou Lab at Massachusetts General Hospital (MGH) and Harvard Medical School, with affiliation to the Broad Institute of MIT and Harvard, invites applications for Postdoctoral positions in Statistical Genetics and Method Development.
The positions offer opportunities to develop robust, scalable statistical methods and computational tools for single-cell omics and the genetics of disease progression. Postdoctoral researchers will lead independent methods and software projects, work with large-scale single-cell studies and biobank cohorts, and collaborate with researchers in the United States and internationally.
Postdoctoral Opportunities in Statistical Genetics and Method Development
Positions are available immediately.
Designation
Postdoctoral Fellow / Postdoctoral Researcher
Research Area
- Statistical Genetics
- Statistical Genomics
- Computational Biology
- Bioinformatics
- Single-Cell Omics
- Genetics of Disease Progression
- Electronic Health Records (EHRs)
- Statistical and Computational Method Development
- Human Genetics
Location
Boston and Cambridge, Massachusetts, USA
The Zhou Lab is jointly based at the Center for Genomic Medicine, Massachusetts General Hospital and the Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, with connections to Harvard- and MIT-based research communities.
Eligibility / Qualification
Applicants should meet the following requirements:
- A PhD in Statistics, Biostatistics, Mathematics, Computer Science, Computational Biology, Genetics, or a related quantitative field.
- PhD must be completed by the start date.
- Strong quantitative and mathematical foundations.
- Experience in developing statistical or computational methods.
- Programming experience in Python or C++.
- Commitment to reproducible research.
- Strong written and verbal communication skills.
- Ability to work effectively in a collaborative and interdisciplinary research environment.
- Previous experience in genetics or genomics is helpful but not mandatory.
- Researchers from other strong quantitative backgrounds are encouraged to apply.
Job Description
The selected postdoctoral researchers will work on the development of innovative statistical and computational methods in one or both of the following research areas:
1. Single-Cell Omics
Develop context-aware statistical approaches to understand genetic regulation across different cell types, cellular states, and biological conditions.
2. Genetics of Disease Progression
Develop computational and statistical methods that integrate genetic data with longitudinal electronic health records (EHRs) to investigate disease progression, complications, and clinical outcomes.
Postdoctoral fellows will:
- Lead statistical methodology and software development projects.
- Develop robust and scalable computational methods.
- Work with large-scale single-cell datasets and biobank cohorts.
- Establish and pursue independent research directions.
- Collaborate with computational biologists, geneticists, bioinformaticians, statisticians, and clinicians.
- Have opportunities for international scientific collaborations.
- Contribute actively to the lab’s research environment and culture.
- Receive close, individualized mentorship from Dr. Zhou.
- Have opportunities for joint mentorship with other faculty members.
- Benefit from expertise across MGH, Harvard, Broad Institute, MIT, and collaborating research groups.
The lab provides an interdisciplinary and supportive environment where researchers are encouraged to share ideas, develop independent scientific interests, and pursue their long-term career goals.
How to Apply
Interested candidates should apply by email.
Please send the following materials to:
Email: wzhou@broadinstitute.org
Application Materials
- Curriculum Vitae (CV)
- Brief statement of research interests
Contact information for references will be requested at a later stage of the application process.
Last Date for Apply
Open until filled / Positions available immediately
Applications are encouraged as soon as possible because positions are currently available.
