Senior Faculty Lead, Digital Pathology Infrastructure and AI Enablement

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Job Description: Senior Faculty Lead, Digital Pathology Infrastructure and AI Enablement, Part Time Department of Pathology Beth Israel Deaconess Medical Center Harvard Medical School, Boston The Department of Pathology at Beth Israel Deaconess Medical Center is seeking a Senior Faculty Lead, Digital Pathology Infrastructure and AI Enablement (Part-Time) f aculty position (Boston) . As a teaching hospital of Harvard Medical School, BIDMC and the Department of Pathology, provide a clinically advanced and supportive academic environment for residents, fellows, and faculty. We're also proud and excited to be an integral part of the landmark collaboration among Dana-Farber Cancer Institute (DFCI), Beth Israel Deaconess Medical Center (BIDMC), and Harvard Medical Faculty Physicians (HMFP) to establish New England's only freestanding adult inpatient cancer hospital. The collaboration will provide unparalleled opportunities for pathologists and other physician specialties to be part of DFCI's internationally recognized cancer team. The candidate will be appointed to the faculty of Harvard Medical School at a part-time academic rank (Lecturer, Instructor, Assistant Professor, Associate Professor) commensurate with experience. Position Summary Reporting to the Director of Digital Pathology (Primary), Department Chair or Vice Chair for Pathology Informatics , t his faculty leadership role builds, scales, and operationalizes BIDMC Pathology's enterprise digital pathology ecosystem and serves as a department-wide expert for AI readiness, evaluation, and clinical deployment in anatomic pathology. The role partners closely with the Director of Digital Pathology key stakeholders (AP leadership, laboratory operations, IT and security, compliance, and research) to ensure safe, validated , high-quality digital workflows and an enduring education and mentorship program. Key R esponsibilities Digital Pathology Infrastructure and Operation s Strategy and Roadmap Lead a multi-year roadmap for whole slide imaging (WSI) and digital sign-out capabilities across BIDMC Pathology (clinical, educational, and research use cases). Define target-state architecture, phased milestones, resourcing, and success metrics. Platform B uild and I ntegration Lead (or co-lead) selection, implementation, and lifecycle management for WSI scanners and a scanning operations model; the image management system and enterprise viewer; storage and archiving ( on-premise and or cloud), networking, identity and access controls; and integration with LIS and EMR worklists and specimen tracking and barcoding workflows. Standardize SOPs across scanning, image QC, downtime procedures, and incident management. Validation, Q uality, and C ompliance Design and oversee validation protocols for primary diagnosis on digital slides (pathologist validation, case set design, discrepancy tracking, competency and re-validation cadence). Build a measurable QA and QC program for tissue-to-image fidelity (staining variability, scanner performance, display calibration, artefact classification, and remediation workflows). Ensure readiness for applicable regulatory and accreditation requirements (for example, CAP, CLIA, HIPAA, and institutional governance). AI Enablement, Evaluation, and Clinical Deployment AI G overnance and S afety F ramework Establish an end-to-end governance model for AI tools used in pathology (selection, risk stratification, validation, monitoring, drift detection, versioning, change control, and retirement). Develop documentation standards and oversight pathways aligned with clinical risk, ethics, and equity principles. AI readiness foundations Build practical infrastructure to support AI translation, including dataset curation pipelines (de-identification, annotation frameworks, ground truth practices); a secure compute environment for evaluation and, where appropriate , model development; and performance benchmarking across representative case mixes and operational conditions. Clinical implementation Partner with clinical subspecialty leads to deploy AI tools into workflow (triage, screening support, quantification, QC augmentation), including user training, acceptance criteria, and post go -live monitoring. Education program development and mentorship Educatio n p rogram Create and lead an ongoing "Digital Pathology and AI in Practice" education program for faculty pathologists and trainees; laboratory staff (histology, accessioning, scanning, and QC); and informatics and IT partners supporting pathology. Curriculum to include validation, workflow redesign, QC, human factors, AI evaluation literacy, and practical guidance on safe and responsible use of AI outputs. Mentorship Mentor trainees and faculty in digital pathology, computational pathology collaboration, and responsible AI adoption. Support scholarly output and career development for learners and junior faculty engaged in digital and AI initiatives. Research, innovation,

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