Postdoctoral Research Fellow

The Dana‑Farber Cancer Institute seeks a POSTDOCTORAL RESEARCH FELLOW, under the Van Allen lab, to work on the analysis of new datasets generated in the context of multiple clinically oriented cancer sequencing projects to help advance precision cancer medicine.

As Dr. Van Allen is the Chief of the Division of Population Sciences, our research effort includes collaborative work with the division faculty members on identification of cancer risk, risk mitigation, early detection, prevention, delivery of cancer care and health policy. The Van Allen lab is an interdisciplinary and highly collaborative laboratory with diverse scientists from various scientific domains leading exciting cancer research.

The qualified candidate will focus on developing new algorithms, including agentic artificial intelligence approaches, for the clinical integration of integrative molecular profiling and large-scale datasets (e.g. pathology images and clinical notes) to enable new discoveries across multiple patient contexts. A specific focus on advancing algorithm development through emerging deep learning techniques is of strong interest. The candidate will also evaluate and integrate existing tools and databases into high-throughput pipelines, and facilitate the display and the distribution of processed data.

• Creation of artificial intelligence algorithms that effectively integrate molecular, pathology/image, and clinical data for prediction and biological discovery
• Prospective clinical sequencing to guide the care of cancer patients
• Studies of coding, non-coding, RNA, and spatial-based drivers of cancer development and treatment response
• Studies of patient samples for tumor behavior and clinical outcomes in context of immunotherapy

This work is a collaborative effort between the Dana‑Farber Cancer Institute, the Broad Institute, and multiple other institutions, aiming to analyze sequencing data to determine the effects of genomic alterations and expression changes on clinical behavior both retrospectively and prospectively. The insights gained will support new approaches for personalized care, clinical decision‑making, biomarker development, and tumor biology.

• A Ph.D. in bioinformatics, genetics, statistics, mathematics, physics, computer science, or comparable research experience with significant experience in machine learning, computer programming, and computational biology.
• A strong background in statistics and biology, and experience managing and curating large datasets with machine learning techniques.
• Excellent oral and written communication skills and the ability to perform both self‑directed and guided research.
• Outstanding personal initiative and ability to work effectively as part of a team.
• Ability to meet deadlines and efficiently multitask.
• Effective collaboration across a range of individuals with variable comfort toward computational biology.
• Ability to seek mentorship and assistance as needed, while also being a mentor to others.

• Background in machine learning
• Background in cancer biology
• Experience with R and/or Python
• Experience with cloud computing
• Willingness to learn new languages and tools as the field grows

This position will involve co‑mentoring of students joining the group, with opportunities for growth in developing multidisciplinary, project‑oriented teams.

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.

The hiring range is based on market pay structures, with individual salaries determined by factors such as business needs, market conditions, internal equity, and the candidate’s relevant experience, skills and qualifications.

For union positions, the pay range is determined by the Collective Bargaining Agreement (CBA).