POSITION SUMMARY/ DEPARTMENT SUMMARY:

The Cell Discovery Network (CDN) at Boston Children’s Hospital is seeking a Computational Biologist or Machine Learning Scientist to lead the development of a framework for modeling and reprogramming rare disease-relevant cell types. This new initiative, inspired by recent progress in human organoid systems, iPSC-based modeling, and single-cell technologies, aims to unlock therapeutic strategies for neglected pediatric diseases by computationally guiding the discovery and modeling of disease-critical cell states.
This position offers the opportunity to integrate cutting-edge computational methods (e.g., generative models, foundation models, optimal transport) with a deep understanding of human developmental biology and stem cell differentiation.

Key Responsibilities:

• Curate and analyze public and in-house datasets (including organoid and iPSC-derived models).
• Identify rare or disease-associated cell types from large-scale single-cell and organoid datasets.
• Determine where similar phenotypes have been observed across developmental systems or model organisms.
• Build and apply machine learning and AI models (e.g., generative or trajectory-based models, foundation models) to identify and compare rare cell states.
• Model cellular trajectories and propose reprogramming strategies to reach desired cell phenotypes from accessible starting points (e.g., iPSCs).
• Prioritize therapeutic strategies for disease modeling and compound screening.

MINIMUM QUALIFICATIONS

Education:

• Bachelor’s Degree is required.
• Ph.D. (or equivalent experience) in computational biology, bioinformatics, machine learning, systems biology, or a related field is preferred.

Experience:

• 4-year STEM Bachelor’s degree or 4-years of STEM experience.
• Minimum of two years of position-specific experience might potentially include experience acquired through MSc or Ph.D. studies.

Boston Children’s Hospital offers competitive compensation and unmatched benefits including flexible schedules, affordable health, vision and dental insurance, child care and student loan subsidies, generous levels of time off, 403(b) Retirement Savings plan, Pension, Tuition and certain License and Certification Reimbursement, cell phone plan discounts and discounted rates on T-passes. Experience the benefits of passion and teamwork.

• Curate and analyze public and in-house datasets (including organoid and iPSC-derived models).
• Identify rare or disease-associated cell types from large-scale single-cell and organoid datasets.
• Determine where similar phenotypes have been observed across developmental systems or model organisms.
• Build and apply machine learning and AI models (e.g., generative or trajectory-based models, foundation models) to identify and compare rare cell states.
• Model cellular trajectories and propose reprogramming strategies to reach desired cell phenotypes from accessible starting points (e.g., iPSCs).
• Prioritize therapeutic strategies for disease modeling and compound screening