Senior Scientist, Computational Imaging and Data Analysis

Dana-Farber Cancer Institute•Boston, MA

36d•$95,000 - $125,100

About The Position

The Center for Immune Oncology (CIO) at the Dana Farber Cancer Institute (DFCI) seeks a highly motivated Senior Scientist to support advanced analytics and data integration efforts across imaging, spatial proteomics, and high-dimensional cytometry data. The successful candidate will play a key role in processing, analyzing, and modeling complex biomedical data - integrating spatial imaging, CyTOF, and clinical data - to enable discovery and translational research collaborations within the CIO. 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 physicians/researchers, and we work with amazing partners, including other Harvard Medical School-affiliated hospitals. The position offers opportunities to collaborate across a diverse set of projects within the Center for Immuno-Oncology (CIO), working closely with experts in computational biology, immunology, and clinical research. The Scientist II/Senior Scientist will sit within the Department of Data Science (DS) and be mentored by faculty directors from both CIO and DS. They will contribute within a small team to data-driven discovery, developing robust and scalable analytic tools for translational research. At Dana-Farber Cancer Institute, we work every day to create an innovative, caring, and inclusive environment where every patient, family, and staff member feels they belong. As relentless as we are in our mission to reduce the burden of cancer for all, we are equally committed to diversifying our faculty and staff. Cancer knows no boundaries and when it comes to hiring the most dedicated and diverse professionals, neither do we. If working in this kind of organization inspires you, we encourage you to apply. 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. EEOC Poster

Requirements

Proficiency in R and/or Python, with experience in reproducible data analysis workflows.
Demonstrated ability in data wrangling, transformation, and integration of heterogeneous data sources.
Experience working in computational immunology. Human immuno-oncology research in an academic or industry setting analyzing clinical trial biomarkers is a plus.
Hands-on experience with image analysis and processing, particularly in biological or clinical imaging contexts.
Strong understanding of statistical modeling and computational methods for large datasets.
Experience working in Unix/Linux cluster environments, using Git/GitHub, and containerized workflows (e.g., Docker, Singularity).
Proficiency with reproducible research and reporting tools such as Jupyter, R Markdown, Quarto, and Posit Connect (or similar).
Strong communication and collaboration skills, including ability to document, present, and explain complex analyses to multidisciplinary teams.
Advanced degree (PhD) in bioinformatics, computational biology, data science, biostatistics, or a related field. 6+ years experience post education and 1+ year management responsibility.
A good working knowledge of molecular and disease biology, especially familiarity with immunology.
Familiarity with medical informatics, clinical data standards, or REDCap API/database programming.

Nice To Haves

Experience with spatial omics, single-cell data, or multimodal integration in human disease contexts.

Responsibilities

Perform imaging and image analysis for spatial proteomics and multiplexed imaging datasets.
Conduct CyTOF and FCS data analysis, including data preprocessing, normalization, clustering, and visualization.
Analyze medical record data, integrating structured and unstructured clinical information as appropriate.
Manage and wrangle large, multimodal datasets, including high-resolution images and patient-level data.
Support database integration, including interoperability and linkage with REDCap and other institutional data systems.
Provide analytic and statistical support for CIO projects - emphasizing development of custom models, analytical pipelines, and reproducible outputs for collaborative teams.
Develop and deliver high-quality graphics and visualizations to communicate findings effectively to both scientific and clinical collaborators.

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