Postdoctoral Research Fellow - Michor Lab

The lab of Prof. Franziska Michor, PhD at the Dana-Farber Cancer Institute (Department of Data Science) & Harvard University (Departments of Biostatistics and Stem Cell and Regenerative Biology) is looking for curious, mathematically-minded researchers to push the frontier of AI and computational biology in healthcare and biomedicine.

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.

• Probabilistic generative models (VLMs, diffusion, flow models)
• Reinforcement learning & Markov decision processes
• Causal inference & counterfactual reasoning
• Mechanistic & physics-informed modeling
• Agentic AI systems for optimizing adaptive, temporal, high-dimensional systems

• Multimodal biomedical data (omics, medical images, histopathology, single cell/bulk, spatial omics)
• Clinical patient trajectories, treatment schedules, and outcomes (survival, resistance, response)

• Patient digital twins
• Virtual AI clinicians
• Virtual cells, tumors, and organs
• Tumor evolution models
• Virtual clinical trials
• Large-scale virtual hospital environments

The Research Fellow will conduct independent and collaborative research under the guidance of a faculty mentor or principal investigator. Responsibilities include designing and executing research projects, analyzing and interpreting data, contributing to manuscripts and presentations, and participating in lab or program activities. The Research Fellow is expected to stay current with relevant literature, adhere to research protocols and ethical standards, and support grant-related or collaborative initiatives as needed.

• Have a PhD in computer science, statistics, applied math, computational biology or related discipline
• Strong programming fundamentals and statistics knowledge
• Interest & knowledge about oncology &immunology, molecular & cellular mechanisms
• Work with ML + generative AI + GPUs at scale
• Experience with clinical or biomedical data and workflows
• Enjoy multimodal + real-world data
• Are excited about high-impact biomedical problems and clinical translation
• Have a strong publication record in math, statistics, or ML/AI 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 committed to having faculty and staff who offer multifaceted experiences. Cancer knows no boundaries and when it comes to hiring the most dedicated and compassionate 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.

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).

$72,000.00 - $76,385.00