
Postdoctoral Associate, Medicine/Computational Biomedicine
Boston, MAFull-time$68–70K/yrSeen todaySeen in employer's feed today
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Requirements
Credentials this posting asks for.
Job overview
The Zhang Lab at Boston University seeks Computational Biology Postdoctoral Associates to study immuno-oncology, kidney disease, or aging. Scholars will develop computational and bioinformatics methods and integrate high-throughput biological, omics, and biomedical imaging data. The lab offers dedicated computational equipment funding, conference support, and an interdisciplinary research environment.
Skills & qualifications
Skills
Qualifications
Full job description
Postdoctoral Associate, Medicine/Computational Biomedicine
Job Description
Postdoctoral Associate, Medicine/Computational Biomedicine
Category
Boston University Medical Campus --> Postdoctoral
Job Location
Boston, Massachusetts, United States
Tracking Code
26599938261103
Posted Date
11/3/2026
Minimum Salary
$67,500.00
Maximum Salary
$70,000.00
The salary of the finalist selected for this role will be set based on a variety of factors, including but not limited to departmental budgets, qualifications, experience, education, licenses, specialty, training and internal pay comparison. The above hiring range represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting.
Position Type
Full-Time/Regular
The Zhang Lab within the section of computational biomedicine at Boston University Chobanian & Avedisian School of Medicine is seeking multiple Computational Biology Postdoctoral Associates interested in studying immuno-oncology, kidney disease, or aging. Postdoctoral scholars will lead the development of novel computational and bioinformatics methods and integrate diverse types of high-throughput biological, omics, and biomedical imaging data generated by the lab and its collaborators.
The position offers dedicated funding for computational equipment and support to attend national and international conferences. The lab provides an interdisciplinary research environment with opportunities to develop innovative computational methods and apply them to important biological and biomedical questions.
Responsibilities:
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Develop principled methods, based on deep learning and advanced mathematical modeling techniques to address biological questions.
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Analyze massive functional genomics data at single cell and population levels.
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Analyze large cohorts of pathological imaging and spatial transcriptomics data.
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Prepare manuscripts and scientific reports.
Required Skills
Qualifications
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PhD in Computational Biology, Computer Science, Biostatistics, Mathematics or other related quantitative areas.
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Experience with teamwork and group communication.
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Experience with self-guided learning in a quickly evolving technical environment.
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Experience in kidney disease, melanoma, AD, microbiome, or other relevant disease areas is preferred.
Additional Preferred Qualifications Related to Potential Projects:
Microbiome and metagenomics: Familiarity with 16S rRNA or shotgun metagenomic data analysis, commonly used microbiome identification and profiling tools, and microbiome metabolic analysis. Experience studying microbiome-host or microbiome-microenvironment interactions is preferred.
Biomedical imaging analysis: Experience with biomedical image analysis, including histopathology images (e.g., H&E), spatial transcriptomics, image processing, segmentation, and classification. Experience with multimodal data integration, such as integrating imaging and molecular data or combining different imaging modalities, is highly desirable. Experience with image registration and 3D reconstruction is preferred.
Deep learning and mathematical modeling: Strong background in deep learning and/or mathematical modeling, with familiarity with graph neural networks, diffusion models, flow matching, and optimal transport.
To Apply:
Please send a letter of interest, current CV and the names and contact information for three references to Dr. Chao Zhang at [email protected] (https://apptrkr.com/get\_redirect.php?id=9939497&targetURL=mailto%3Achz2009%40bu.edu) .
We are an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, natural or protective hairstyle, religion, sex, age, national origin, physical or mental disability, sexual orientation, gender identity, genetic information, military service, pregnancy or pregnancy-related condition, or because of marital, parental, or veteran status. We are a VEVRAA Federal Contractor.
Job Location: Boston, MA
Position Type: Full-Time/Regular
Salary Grade: $67,500.00-$70,000.00
To apply, visit https://jobs.silkroad.com/BU/Faculty/jobs/317509 (https://apptrkr.com/9939497)
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How this job compares
Set against the 804 open Postdoctoral Researcher jobs on Olive Jobs, counted November 4, 2026.
- Pay
- This posting$68–70K/yr
- Massachusetts median$68–80K/yr90 salary ranges
- US median$69–80K/yr391 salary ranges
This range's midpoint, $69K, is 7% below the Massachusetts median midpoint ($74K) — in the lowest quarter of Postdoctoral Researcher salary ranges in Massachusetts.
- Openings
- Olive Jobs lists 110 open Postdoctoral Researcher jobs in Massachusetts and 804 across the US. Under 1% of them nationwide are listed as remote or flexible.
- Hiring the most in Massachusetts
- Harvard University62 open
- Mass General Brigham17 open
- Dana-Farber Cancer Institute13 open
- Experience
- Postdoctoral Researcher postings that state a minimum ask for 1 year of experience at the median; the middle half ask for 0 to 3 years (55 postings).
- Education
- This posting asks for a doctorate or professional degree; 670 of the 804 open Postdoctoral Researcher jobs (83%) ask for a doctorate or professional degree.
Counted across the open, public US postings on Olive Jobs on November 4, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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