ZipRecruiter

Log In

1

Python Biology Jobs in Massachusetts (NOW HIRING)

next page

Showing results 1-20

All JobsPython Biology JobsPython Biology Jobs in Massachusetts

Python Biology information

What is the difference between Python Biology vs Bioinformatics Analyst?

AspectPython BiologyBioinformatics Analyst
Required CredentialsBiology degree, Python programming skillsBiology or related degree, Python and data analysis skills
Work EnvironmentResearch labs, biotech companies, academic institutionsResearch institutions, biotech firms, healthcare organizations
Industry UsageData analysis, modeling biological systems using PythonAnalyzing biological data, developing pipelines, interpreting results

Python Biology focuses on applying Python programming to biological research, often emphasizing coding and data modeling. Bioinformatics Analysts combine biological knowledge with data analysis skills, including Python, to interpret complex biological datasets. Both roles require programming skills and work in similar environments, but Python Biology is more research and development-oriented, while Bioinformatics Analysts focus on data interpretation and analysis.

How do Python Biology professionals typically collaborate with interdisciplinary teams in research settings?

Python Biology professionals often work closely with biologists, data scientists, and software engineers to analyze complex biological data. Collaboration usually involves translating biological questions into computational tasks, developing data pipelines, and presenting findings in a way that is accessible to both technical and non-technical stakeholders. Regular meetings and code reviews are common practices, ensuring that the software developed aligns with the scientific goals of the project. This interdisciplinary approach not only enhances research outcomes but also provides valuable learning and growth opportunities for team members.

What are the key skills and qualifications needed to thrive as a Computational Biologist specializing in Python, and why are they important?

To thrive as a Computational Biologist with a focus on Python, you need a strong background in biology, bioinformatics, and programming, typically supported by a degree in biological sciences, computer science, or a related field. Familiarity with Python libraries like Biopython, NumPy, and pandas, as well as experience with data analysis tools and version control systems such as Git, is essential. Analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting biological data and collaborating with interdisciplinary teams. These competencies enable accurate data analysis, innovative research, and effective teamwork in advancing biological discoveries.

What is a Python biologist?

A Python biologist is a professional who uses the Python programming language to analyze and interpret biological data. They often work in fields like bioinformatics, genomics, and computational biology, developing software tools to process large datasets such as DNA sequences or protein structures. Python biologists help translate complex biological problems into computational solutions, enabling researchers to gain insights that would be difficult to achieve manually.
What are popular job titles related to Python Biology jobs in Massachusetts? For Python Biology jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Python Biology jobs in Massachusetts look for? The top searched job categories for Python Biology jobs in Massachusetts are:
What cities in Massachusetts are hiring for Python Biology jobs? Cities in Massachusetts with the most Python Biology job openings:
Python Biology jobs near you
Computational Biologist

Computational Biologist

University of Massachusetts Medical School

Worcester, MA

$80K - $90K/yr

Full-time

Posted 25 days ago

Job description

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:

  1. 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.
  2. 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.


Responsibilities

  • 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

  • Master’s 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


Apply