Associate Computational Biologist

The Associate Computational Biologist is training to become a Computational Biologist. They are responsible for routine data analysis or processing of biological data, with a focus on high-throughput technologies and genomic databases, under the supervision of a mentor. The Computational Biologist is a quantitative scientist who collaborates with scientific investigators and with other research staff in the analysis of high-throughput data, and dissemination of scientific results.

The Computational Biologist may work on many types of projects and areas of research including cancer genomics, functional genomics, immuno-oncology, molecular imaging, data management and integration, and querying biological databases.

• Build data processing pipelines to convert raw data into formats compatible with conventional statistical analysis and visualization under supervision of mentor.
• Follow a detailed manual to perform routine data analysis.
• Monitor, download, organize, and manage data from public data repositories or generated by collaborators.
• Help prepare tables and figures for manuscript preparation.
• Train to develop timelines and components for multiple routine projects; master multi-tasking so that complex projects involving many interdisciplinary individuals move forward smoothly.
• Work with postdoctoral mentor Priyanka Sharma to complete ribosome profiling analysis from start to final graphs, including building genotype‑specific RNA expression maps, predicting novel open reading frames for interpretation of immunopeptidomic data.
• Collaborate with Priyanka to expedite analysis of direct RNA long‑read sequencing data for gene expression and RNA modifications, with the goal of submission by February 2027.
• Complete single‑cell RNA sequencing pipelines for mutant and wild‑type CDK
  13 patient samples; help identify the correct controls for the literature and take ownership of this part of the project.

• Knowledge of UNIX/Linux; familiarity with scripting in Python and statistical programming using R.
• Familiarity with principles of experimental design and modern data analysis paradigms.
• Ability to discuss and present results, share ideas accurately, and communicate them effectively, both in writing and verbally with supervisory oversight.
• Strong interpersonal skills – ability to effectively interact with all levels of staff and external contacts.
• Excellent analytical, organizational, and time‑management skills.

The position requires a bachelor’s degree in a STEM field; no prior experience necessary.

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Dana‑Farber Cancer Institute is an equal‑opportunity employer and affirms the right of every qualified applicant to receive consideration for employment without regard to race, color, religion, sex, gender identity or expression, national origin, sexual orientation, genetic information, disability, age, ancestry, military service, protected veteran status, or other characteristics protected by law.

Pay Transparency Statement:
The hiring range is based on market pay structures, with individual salaries determined by factors such as business needs, market conditions, internal equity, and based on the candidate’s relevant experience, skills and qualifications. For union positions, the pay range is determined by the Collective Bargaining Agreement (CBA).

$60,000.00 – $67,466.00