Postdoctoral Associate, Computational Biomedicine

Boston University; Boston (MA); On-site; USD 68,000 - 70,000; Full time

Job summary

Boston University Beane Lab within the computational biomedicine section seeks a highly motivated postdoctoral associate to lead analysis of single-cell and spatial transcriptomic data across translational projects in lung and urethral disease. You will collaborate with a multidisciplinary team and take ownership from data processing to biological interpretation and publication.

The role requires a PhD in a quantitative field and hands-on experience with single-cell/spatial data, proficiency in

Qualifications

• PhD in computational biology, bioinformatics, genomics, biostatistics or related quantitative field (last 3 years or with start date imminent).
• Hands-on experience analyzing single-cell and/or spatial transcriptomics with first-author work (publication/preprint).
• Proficiency in R and/or Python and frameworks (Seurat, Bioconductor, scanpy, squidpy, scvi-tools); comfort with Linux/HPC.
• Excellent written and verbal English communication; able to work independently and in a multidisciplinary team.

Responsibilities

• Lead analysis of single-cell and spatial transcriptomic data from processing to biological interpretation and publication.
• Collaborate with a multidisciplinary team of computational biologists, bench scientists, pathologists, and clinicians.

Skills

Single-cell & spatial transcriptomics

R & Python proficiency

Linux / HPC experience

English communication

Publication record

Education

PhD in computational biology or related field

Tools

Seurat

Bioconductor

scanpy

squidpy

scvi-tools

Nextflow

Snakemake

Git

Job description

Postdoctoral Associate, Computational Biomedicine

Category

Boston University Medical Campus --> Postdoctoral

Job Location

Tracking Code

26599938201023

Posted Date

10/23/2026

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 Beane Lab within the section of computational biomedicine at Boston University Chobanian & Avedisian School of Medicine is seeking a highly motivated computational postdoctoral associate to lead the analysis of single-cell and spatial transcriptomic data across two translational research programs in lung and urethral disease. The successful candidate will join a collaborative group of computational biologists, bench scientists, pathologists, and clinicians, and will take intellectual ownership of projects from data processing through biological interpretation and publication.

Required Skills

Required

• PhD (or equivalent) in computational biology, bioinformatics, genomics, biostatistics, systems biology, or a related quantitative field, obtained within the last [3] years or expected before the start date.
• Hands-on experience analyzing single-cell and/or spatial transcriptomic data, with a first-author publication or preprint demonstrating this work.
• Proficiency in R and/or Python and standard analysis frameworks (e.g., Seurat, Bioconductor, scanpy, squidpy, scvi-tools), and comfort working in a Linux/high-performance computing environment.
• Working knowledge of, or a strong willingness to learn, the underlying biology, including epithelial and immune cell biology, tissue histology, and the pathophysiology of lung and urethral disease.
• Excellent written and verbal communication skills in English and the ability to work both independently and as part of a multidisciplinary team.

Preferred

• Background in cancer biology, immunology, pulmonary or urologic disease, or tissue pathology.
• Experience with multimodal data integration, spatial neighborhood analysis, or machine learning applied to genomic or imaging data.
• Experience with workflow management (e.g., Nextflow, Snakemake), containers, and version control (Git).

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.