Postdoctoral Fellow – AI & Computational Hematology

Overview

About Us:

Memorial Sloan Kettering Cancer Center (MSK) unites a singular mission: ending cancer for life. Our specialized care teams provide personalized, compassionate, expert care to patients of all ages. Informed by basic research at our Sloan Kettering Institute, scientists across MSK collaborate to conduct translational and clinical research to improve prevention, diagnosis, and treatment of cancer. MSK is dedicated to training the next generation of scientists and clinicians who pursue our mission at MSK and around the globe.

The HemeAI Lab at Memorial Sloan Kettering Cancer Center (MSKCC) is a clinical translational research laboratory focused on transforming cancer diagnosis, risk stratification, and disease monitoring through artificial intelligence. Our mission is to improve patient outcomes in leukemias and other hematologic diseases by developing clinically deployable, AI-powered tools that benefit MSKCC patients and have potential for global clinical adoption and commercialization.

MSKCC is a world-leading cancer center with clinical data, infrastructure, and multidisciplinary expertise, providing an environment for high-impact translational research.

We are seeking highly motivated postdoctoral fellows to join our interdisciplinary team led by Gregory Goldgof, MD, PhD, MS, Director of Artificial Intelligence for the Hematopathology Service. This is a paid postdoctoral position offering substantial independence, access to large-scale real-world clinical datasets, and close integration with clinical practice.

Postdoctoral fellows will play a central role in developing and validating AI systems for medical image analysis, LLM-based tooling, and multimodal clinical data integration, with opportunities to lead projects, publish in high-impact journals, and contribute to clinically deployed and commercial-grade systems.

Applicants should have strong interest and experience in one or more of the following areas:

• Deep learning for medical image analysis (Python, PyTorch)
• Multiple instance learning for pathology whole slide images (WSIs)
• Classical computer vision
• Multimodal data integration for outcome prediction
• AI model calibration to real world deployments
• Full-stack web development for clinical and research applications (JavaScript, HTML, CSS, Django)
• MLOps / Dev Ops (Docker, Unix-based systems)
• Cloud-based deployment and scalable infrastructure (Docker, AWS)
• Human–Computer Interaction (HCI) and clinical interface design
• Data science and analytics (Python, SQL)
• Collaborative software development (Git Hub)

• Automated detection, quantification, and qualitative characterization of cancer cells in blood, bone marrow, H&E tissue, and cytology specimens from whole-slide and microscope images
• Clinical outcome prediction using multimodal clinical data (images, genetics, laboratory values, etc.)
• Discovery of novel morphologic and computational biomarkers
• Transformation of unstructured clinical data into structured datasets
• Clinical validation and trials of diagnostic, prognostic, and medical decision-support algorithms

Postdoctoral fellows will work closely with MSKCC clinical services and maintain active collaborations with external partners at UC San Francisco and UC Berkeley Statistics, providing exposure to diverse datasets, methodologies, and interdisciplinary mentorship.

• PhD, MD/PhD, or equivalent doctoral degree in computer science, biomedical engineering, computational biology, medical physics, or a related field
• Prior experience in deep learning, computer vision, or medical imaging. Experience with pathology images strongly preferred.
• Demonstrated ability to conduct independent research and publish in peer-reviewed venues
• Demonstrated ability to leverage AI-assisted programming to rapidly prototype, iterate, and deploy beta versions of research tools

• Strong translational and clinical deployment focus
• Opportunities for first-author publications
• Mentorship toward academic, industry, and entrepreneurial career paths
• Direct access to…