Computational Biologist: Autoimmune Multi-Omics & Genomics

UMass Med School; Worcester (MA); On-site; USD 80,000 - 90,000; Full time

Job summary

UMass Med School in Worcester, MA seeks a Computational Biologist to join an interdisciplinary team studying autoimmune diseases. You will analyse bulk and single-cell datasets, and integrate multi-omic and clinical data to model disease mechanisms.

The role combines computational and statistical work with a biology-driven mindset, requiring strong programming in R/Python and experience in modern omics analyses.

Qualifications

• Master's degree in quantitative field; Ph.D. preferred.
• 1–3 years of related experience.
• Proficiency in R or Python for analysis and visualization.
• Experience with linear/mixed models and ML approaches.

Responsibilities

• Process, analyze, and interpret large-scale datasets (bulk/single-cell RNA-seq, ATAC-seq, proteomics, spatial transcriptomics).
• Develop new analysis methods as needed during investigations.
• Perform clustering, trajectory inference, and regulatory network reconstruction.
• Collaborate with clinicians and immunologists to form testable hypotheses.
• Integrate genetic, molecular, and clinical features for mediation and causal inference.
• Model temporal dynamics using wearable and clinical data.
• Present results in meetings and conferences; contribute to manuscripts.
• Generate publication-quality figures and interactive visualizations.

Skills

Statistical modeling

Data visualization

Machine learning approaches

R

Python

Unix/Linux

HPC / Cloud computing

Education

Master's degree in Computational Biology or related field

Ph.D. strongly preferred

Tools

R

Python

Unix/Linux

HPC / Cloud

Job description

UMass Med School in Worcester, MA seeks a Computational Biologist to join an interdisciplinary team studying autoimmune diseases. You will analyse bulk and single-cell datasets, and integrate multi-omic and clinical data to model disease mechanisms.

The role combines computational and statistical work with a biology-driven mindset, requiring strong programming in R/Python and experience in modern omics analyses.