Jobloria
Computational Biologist
UMass Medical School
Location : Worcester, MA, 01608
Job Type : Full Time
Salary : $90,000.00/Yr
Date Posted : 2 December 2025
Job Number: 2025-48967
Category:Research
Location: Worcester, MA
Shift:Day
Exempt/Non-Exempt:Exempt
Business Unit:UMass Chan Medical School
Department:School - Genomics and Computational Biology - W403700
Job Type:Full-Time
Num. Openings: 1
Post Date: Nov. 12, 2025
Work Location:100% Onsite
Salary Minimum:USD $80,000.00/Yr.
Salary Maximum:USD $90,000.00/Yr.
Apply
Refer a Friend
Back
Computational Biologist
Job Number: 2025-48967
Category:Research
Location: Worcester, MA
Shift:Day
Exempt/Non-Exempt:Exempt
Business Unit:UMass Chan Medical School
Department:School - Genomics and Computational Biology - W403700
Job Type:Full-Time
Num. Openings: 1
Post Date: Nov. 12, 2025
Work Location:100% Onsite
Salary Minimum:USD $80,000.00/Yr.
Salary Maximum:USD $90,000.00/Yr.
The Computational Biologist be part of an interdisciplinary research group combining systems biology, immunology, and human genetics to uncover the mechanisms that drive autoimmune disease. The lab leads large-scale efforts such as the VIGOR family-based vitiligo cohort (bigor.umassmed.edu) and multi-omic studies of lupus and cutaneous autoimmunity, integrating data across molecular, cellular, and clinical scales.
This position will bridge two complementary areas of research:
- Molecular systems immunology, involving the analysis of single-cell and spatial transcriptomic, epigenomic, and proteomic datasets to dissect cell states and communication networks in diseased and healthy tissues.
- Genetic and longitudinal modeling, integrating genomic variation with real-world longitudinal data—including proteomics, wearable device metrics, survey responses, and clinical measures—to build predictive and causal models of disease initiation and progression.
The ideal candidate combines strong computational and statistical skills with a biological curiosity about how genetic and environmental factors jointly shape immune dysregulation.
- Process, analyze, and interpret large-scale datasets including bulk and single-cell RNA-seq, ATAC-seq, proteomics, and spatial transcriptomics.
- Develop new analysis methods as needed and as they arise during investigations
- Perform clustering, trajectory inference, and regulatory network reconstruction to define immune cell states and pathways relevant to autoimmune pathogenesis.
- Work closely with clinicians, immunologists, and experimentalists to formulate biologically grounded hypotheses and computational analyses.
- Integrate genetic, molecular, and clinical features to identify mediators linking genotype to phenotype using mediation and causal inference frameworks (e.g., Bayesian networks).
- Combine data from wearable sensors (e.g., Fitbit activity, sleep, heart rate), clinical surveys, and biomarker measurements to model temporal dynamics of disease activity.
- Present findings in lab meetings, consortium calls, and scientific conferences; contribute to manuscripts and grant proposals.
- Generate publication-quality figures and interactive visualizations that communicate complex data intuitively.
Required Qualifications
- Masters degree in Computational Biology, Bioinformatics, Genetics, Statistics, Physics, Math or a related quantitative field; Ph.D. strongly preferred.
- 1-3 years of related experience
- Strong proficiency in R or Python, statistical modeling, and data visualization.
- Strong understanding of linear models, mixed-effect models, and in general machine learning approaches to complex datasets.
- Experience working in Unix/Linux environments and using HPC or cloud-based computational resources.
Preferred Qualifications
- Background in human genetics or clinical genomics, including genotype imputation, association testing, and fine-mapping.
- Experience with integrative or multi-omic data analysis and familiarity with single-cell and spatial transcriptomic data.
- Knowledge of causal inference, longitudinal modeling, or Bayesian hierarchical modeling.
- Exposure to wearable-device or digital-phenotyping datasets and experience linking such data to molecular or clinical outcomes.
- Understanding of immunology or autoimmune disease biology.
- Familiarity with containerization (Docker/Singularity), workflow management systems (Snakemake, Nextflow), and reproducible-research practices.
#LI-KR1
Posting Disclaimer:
This job posting outlines the primary responsibilities and qualifications for the role but is not intended to be an exhaustive list. Duties and expectations may evolve in response to the needs of the department and the broader institution.
In alignment with our commitment to pay transparency, the base salary range for this position is listed above (exclusive of benefits and retirement). At UMass Chan Medical School, final base salary offers are determined based on a combination of factors, including your skills, education, and relevant experience. We also consider internal equity to ensure fair and consistent compensation across our teams.
Please note that the range provided reflects the full base salary range for this position. Offers are typically made within the midrange to allow for future growth and development within the role.
In addition to base pay, UMass Chan offers a comprehensive Total Rewards package, which includes paid time off, medical, dental, and vision coverage, and participation in a 401(a)-retirement plan, with the option to contribute to a voluntary 403(b) plan.
UMass Chan welcomes all qualified applicants and complies with all state and federal anti-discrimination laws.
Freqently Asked Questions
Techniques such as single-cell RNA-seq analysis, trajectory inference, and Bayesian networks excel in dissecting complex immune cell interactions and genetic influences in autoimmune disease, aligning well with interdisciplinary research goals at UMass Medical School’s genomics department.
By combining metrics like heart rate and activity levels from wearables with genetic and proteomic information, computational biologists can build dynamic models that reveal how environmental factors influence immune dysregulation and disease timelines, enhancing predictive insights.
A Computational Biologist focuses more on interpreting biological data with strong statistical modeling, including causal inference and longitudinal studies, rather than just managing bioinformatics pipelines, requiring deep understanding of immunology and genetics.
While formal certifications aren’t mandatory, expertise in genomic data analysis tools, proficiency with HPC environments, and familiarity with workflow managers like Snakemake enhance competitiveness for computational biology roles in Worcester’s academic research scene.
Worcester hosts a growing biotech and research community, but positions like those at UMass Medical School are competitive due to specialized skill requirements in genomics and immunology, demanding candidates with strong interdisciplinary computational experience.
UMass Medical School fosters collaboration across genomics and immunology, providing access to high-performance computing, multi-omic datasets, and mentorship opportunities, enabling computational biologists to innovate in autoimmune disease studies effectively.
Absolutely, candidates are encouraged to create novel analytical methods and visualization tools tailored to their research questions, enhancing the lab’s ability to explore complex biological networks and disease mechanisms with cutting-edge approaches.
The position offers a competitive salary between $80,000 and $90,000 annually, reflecting the specialized expertise required in computational biology, genomics, and immunology within Worcester’s academic research environment.
Careers emphasizing multi-omic data integration, statistical modeling, and collaborative research in immunology or genetics closely match the daily responsibilities, enabling professionals to contribute to cutting-edge autoimmune disease research.
UMass Medical School offers a uniquely interdisciplinary setting, blending clinical genomics with systems immunology, which provides computational biologists with diverse datasets and collaborative projects not always available in conventional research environments.
Popular Searches for Computational Biologist