Computational and Digital Pathology Slides

The Computational and Digital Pathology Fellowship Program at Moffitt Cancer Center provides advanced training at the intersection of pathology, artificial intelligence, digital pathology, translational pathology and precision oncology.

As cancer care increasingly relies on digital technologies and data-driven decision-making, pathologists must be prepared to lead the development, validation, implementation and evaluation of innovative computational tools. This two-year non-accredited fellowship offers immersive training in digital pathology workflows, image analysis, machine learning, computational diagnostics and translational research within an NCI-designated Comprehensive Cancer Center.

Fellows collaborate with pathologists, clinicians, pharmacists, data scientists, machine learners, bioinformaticians and translational researchers to develop solutions that improve cancer diagnosis, biomarker discovery, prognostication and treatment selection. Through a combination of hands-on clinical experience, mentored research and exposure to operational digital pathology systems, fellows gain the expertise needed to become leaders in the rapidly evolving field of computational pathology.

Moffitt's unique environment provides access to large-scale oncology datasets, enterprise digital pathology platforms, advanced imaging technologies and multidisciplinary research programs focused on improving patient outcomes.

Why Choose Moffitt for Your Fellowship?

A Premier Cancer Center

Moffitt Cancer Center and Research Institute is one of the nation's leading NCI-designated Comprehensive Cancer Centers, with a singular focus on the prevention and cure of cancer. Fellows train in a highly collaborative environment where clinical care, translational research and education are fully integrated.

State-of-the-Art Digital Pathology Infrastructure

Moffitt operates with a nearly fully digital pathology platform, with numerous high-throughput whole slide imaging scanners, integrated clinical workflows and advanced image management and analysis software already in use. The Advanced Analytical and Digital Laboratory performs spatial transcriptomics, multiplex immunofluorescence and digital image analysis. All of the resources necessary, from scanner to sign-out to model development, are ready for fellow use.

Multidisciplinary Collaboration

Fellows train with faculty across Anatomic and Molecular Pathology, Hematopathology, Machine Learning, Integrated Mathematical Oncology, Bioinformatics, Biostatistics, and Translational Pathology, with hands-on access to the Advanced Analytical and Digital Laboratory. Collaborative projects span AI validation, spatial transcriptomics and digital biomarker discovery to translate into real-world clinical solutions.

Innovation in Artificial Intelligence

Moffitt is one of the few cancer centers with dedicated departments of Machine Learning and Integrated Mathematical Oncology, placing AI development at the core of its research enterprise. The institution has invested in the infrastructure to match, including high-performance computing and an Advanced Analytical and Digital Laboratory with spatial transcriptomics and high-throughput scanning capabilities. Active industry partnerships and multi-institutional AI validation studies bring fellows into projects with real-world reach. This fellowship sits at the intersection, giving trainees a front-row seat to how AI is being constructed and deployed in cancer care.

Comprehensive Research Opportunities

Fellows have access to a full digital pathology and computational infrastructure, from whole slide imaging and spatial transcriptomic platforms to high-performance computing. Research spans algorithm development, AI validation and spatial biology, with protected time to pursue an independent project through manuscripts and presentations. Fellows can build on existing faculty projects or develop their own, ranging from training deep learning models for diagnosis and prognosis, building foundation models, digital biomarker discovery and multimodal integration of imaging with molecular data.

Fellowship Experience

The two-year fellowship program blends clinical operations, advanced analytics, research and innovation in a single integrated curriculum. Training covers digital pathology fundamentals, machine learning, spatial transcriptomics and clinical AI integration, with time protected for computational work and clinical service using digital diagnostics. Fellows gain practical experience in evaluating commercial AI tools, navigating regulatory requirements and understanding what it takes to implement digital pathology in practice. Graduates leave positioned to lead in academic medicine, industry, or at the intersection of both.

Two female clinicians looking a specimen on a computer screen

Core Educational Areas

Core educational areas include digital and computational pathology, artificial intelligence and machine learning, clinical image analysis and precision oncology.

Core Educational Areas