Research Technician - Spatial Transcription Comp Bio

Dana-Farber Cancer Institute • Boston, MA

6d • $47,500 - $51,300

About The Position

We are thrilled to offer a unique position for a highly motivated, recent college graduate to join our team at the Molecular Imaging Core at the Dana-Farber Cancer Institute as an early career researcher specializing in computational biology.

This role is an excellent entry point for anyone who is passionate about spatial multiomics data analysis and interested in graduate school in biomedical research. As a computational technician, you will work closely with a team of talented biologists in a collaborative and learning environment. This position provides a platform to work with cutting-edge technologies and contribute to the understanding of complex biological systems and the tumor microenvironment.
Located in Boston and the surrounding communities, Dana-Farber Cancer Institute is a leader in life changing breakthroughs in cancer research and patient care. We are united in our mission of conquering cancer, HIV/AIDS, and related diseases. We strive to create an inclusive, diverse, and equitable environment where we provide compassionate and comprehensive care to patients of all backgrounds, and design programs to promote public health particularly among high-risk and underserved populations. We conduct groundbreaking research that advances treatment, we educate tomorrow's physician/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals.
As a core Data Technician, you will be learning the following skills:
• Implement pipelines for processing, analyzing, and interpreting spatial
multiomics data, including single-cell quantification, gene expression profiling, and network analysis.
• Work with large and complex imaging data sets, utilizing various machine learning, mathematic models, and other data analysis pipelines to derive insights and make data-driven decisions.
• Collaborate with researchers and biologists to develop solutions that can improve our understanding of tumor microenvironment and cell-cell interactions.
• Participate in the development of new spatial single-cell imaging data analysis techniques and software tools to improve data analysis speed and quality.
• Communicate results and findings to various stakeholders, including researchers, biologists, and management team.

Requirements

• Completed (or to be completed in May 2026) bachelor’s degree in a relevant field such as bioinformatics, math, data science, or computer science.
• Proficiency in R and Python.
• Comfortable working with Linux system.
• Excellent communication skills, with the ability to work collaboratively with researchers and biologists.
• Strong problem-solving skills and attention to detail.
• Ability to work independently, with a high level of self-motivation.

Responsibilities

• Implement pipelines for processing, analyzing, and interpreting spatial multiomics data, including single-cell quantification, gene expression profiling, and network analysis.
• Work with large and complex imaging data sets, utilizing various machine learning, mathematic models, and other data analysis pipelines to derive insights and make data-driven decisions.
• Collaborate with researchers and biologists to develop solutions that can improve our understanding of tumor microenvironment and cell-cell interactions.
• Participate in the development of new spatial single-cell imaging data analysis techniques and software tools to improve data analysis speed and quality.
• Communicate results and findings to various stakeholders, including researchers, biologists, and management team.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Number of Employees: 5,001-10,000 employees