Scientist II

Overview

The Scientist II position is part of multiple ongoing interdisciplinary collaborations, the specific work will depend on your expertise and interests. This is an exciting opportunity to contribute to projects with direct real-world impact in cancer precision medicine, leveraging state-of-the-art AI methods, large-scale multi-modal clinical and biomedical data, and high-performance GPU computing

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.

Responsibilities

Examples of tasks you are likely to be engaged in include:

• Collaborate with faculty, postdocs, and research staff to develop, implement, and optimize generative AI and probabilistic models (e.g., LLMs, VLMs, diffusion models) for oncology applications.
• ·Design and implement scalable AI pipelines integrating multi-modal clinical and biomedical data, including EHRs, genomic, single-cell & spatial transcriptomic (e.g. scRNAseq, Visium, Xenium), and in-vitro perturbation datasets.
• Lead projects to build end-to-end AI computational tools for quantitative predictive modeling, treatment outcome prediction, and AI-driven patient case analyses using state-of-the-art AI methods and GPU-accelerated computing.
• Analyze and model complex temporal biological processes (e.g., tumor growth, disease progression, treatment response) to inform model development and validation.
• Develop interpretable AI methods, perform analyses and visualization, and deploy interactive AI tools for researchers and clinicians, while contributing to manuscript preparation.
• Supervis
• e and mentor master’s and undergraduate students, providing guidance on AI methods, statistical and biomedical data analyses, and coding best practices.
• Engage in active collaboration with clinicians, biologists, and computational scientists to translate AI insights into clinically actionable findings.

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)

$92,400 - $104,300

Qualifications

• PhD in a quantitative discipline (e.g., Computer Science, Statistics, Applied Mathematics, or Machine Learning).
• 6-9 years of experience post–bachelor’s degree and a minimum of 2 years of professional experience following PhD completion.
• Proven experience analyzing multi-modal clinical and biomedical data, including large-scale EHRs, genomic alterations, single-cell RNA-seq, spatial transcriptomics platforms such as Visium and Xenium, and in-vitro perturbation data.
• Both theoretical and applied expertise in machine learning, encompassing generative AI (e.g., Large Language Models, Vision-Language Models) and probabilistic models such as diffusion models and neural/normalizing flows.
• Demonstrated ability to write scalable, efficient code and train AI models on GPU-based computing environments.
• Experience supervising master’s and undergraduate students, providing mentorship and project guidance.
• A solid understanding of biological and medical principles—particularly those related to temporal processes such as tumor growth, disease progression, and treatment response and a willingness to learn new concepts in oncology and computational biology.
• Strong communication skills and collaborative mindset with the ability to work effectively with researchers, postdocs, clinicians, and biologists.
• Active participation in interdisciplinary projects, developing advanced computational tools for clinical and biological questions using AI methods, and delivering large-scale, interpretable data analyses.
• Engagement in all lab and departmental meetings at DFCI.
• Proven track record of leading small research teams and presenting scientific work to large and diverse audiences.

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.