Senior Faculty Lead, Digital Pathology Infrastructure and AI Enablement

HMFP at BIDMC, Inc.; United States; On-site; USD 269,000 - 321,000; Part time

Benefits offered by this job

Health insurance

Dental insurance

Vision insurance

Retirement plan

Job summary

The position of Senior Faculty Lead at HMFP at BIDMC, Inc. in the United States involves building a digital pathology ecosystem and enhancing AI capability in clinical pathology. You will lead strategic initiatives, oversee operations, and mentor future leaders in the field.

The ideal candidate possesses an MD or DO with board certification in Anatomic Pathology and is proficient in computational pathology and AI tools. The role offers an annual compensation range of $269,000 – $321,000, alongside comprehensive benefits including health, dental, and retirement plans.

Qualifications

• MD or DO with board certification in Anatomic Pathology needed.
• Proven expertise in computational pathology and informatics is required.
• Experience leading multidisciplinary programs is essential.

Responsibilities

• Lead a multi‑year roadmap for digital pathology.
• Establish an end-to-end governance model for AI tools.
• Develop and manage educational programs for digital pathology.

Skills

Expertise in computational pathology

Strong communication skills

Leadership in multidisciplinary programs

Collaboration across clinical and research domains

Education

MD or DO with board certification in Anatomic Pathology

Tools

AI tools

Image analysis systems

Job description

Position Overview

Senior Faculty Lead, Digital Pathology Infrastructure and AI Enablement (Part‑Time) is a faculty role at Harvard Medical School and Beth Israel Deaconess Medical Center, Boston. The faculty member will build and operationalize BIDMC Pathology’s enterprise digital pathology ecosystem, serve as a department‑wide expert for AI readiness, evaluation and clinical deployment in anatomic pathology, and partner closely with stakeholders to ensure safe, validated, high‑quality digital workflows and an enduring education and mentorship program.

Responsibilities

Digital Pathology Infrastructure and Operations

• Strategy and Roadmap: Lead a multi‑year roadmap for whole slide imaging (WSI) and digital sign‑out capabilities across BIDMC Pathology. Define target‑state architecture, phased milestones, resourcing, and success metrics.
• Platform Build and Integration: Lead selection, implementation, and lifecycle management of WSI scanners, scanning operations model, image management system, enterprise viewer, storage/archiving, networking, identity and access controls, and integration with LIS and EMR workflows.
• Standardization and Validation: Develop SOPs for scanning, QC, downtime procedures, incident management; design and oversee validation protocols for primary diagnosis, build QA/QC program for tissue‑to‑image fidelity, and ensure readiness for CAP, CLIA, HIPAA, and institutional governance.

AI Enablement, Evaluation, and Clinical Deployment

• Governance and Safety: Establish an end‑to‑end governance model for AI tools, including selection, risk stratification, validation, monitoring, drift detection, versioning, change control, and retirement.
• Infrastructure Foundations: Build dataset curation pipelines, secure compute environment, and performance benchmarking across case mixes and conditions.
• Clinical Implementation: Partner with clinical subspecialty leads to deploy AI tools into workflow, including user training, acceptance criteria, and post‑go‑live monitoring.

Education Program Development and Mentorship

• Lead an ongoing “Digital Pathology and AI in Practice” education program for faculty, trainees, lab staff and informatics/IT partners.
• Mentor trainees and junior faculty in digital pathology, computational pathology collaboration, and responsible AI adoption; support scholarly output and career development.

Research, Innovation, and External Collaboration

• Enable clinical‑translational research using high‑quality digital slide repositories and standardized data capture.
• Support grants, publications and multi‑institution collaborations related to digital pathology and AI implementation science.
• Develop and manage academically appropriate industry collaborations aligned with BIDMC policies.

Qualifications

• MD or DO with board certification in Anatomic Pathology (or AP/CP). Eligibility for medical licensure in Massachusetts.
• Demonstrated expertise in computational pathology, pathology informatics, image analysis, artificial intelligence, or related domains.
• Experience leading multidisciplinary programs or initiatives involving clinical, computational, and informatics teams.
• Knowledge of regulatory and quality frameworks for digital and computational pathology systems.
• Track record of scholarly activity, innovation, or program development in computational pathology or informatics.
• Strong communication and change‑management skills.

Preferred Attributes

• Visionary leader capable of advancing data‑driven transformation in pathology at institutional and national levels.
• Dual fluency in medicine and computing or informatics with a portfolio spanning clinical pathology practice and technical infrastructure development.
• Strong collaboration across clinical, research, engineering, and informatics domains.
• Commitment to clinical excellence, innovation, and academic scholarship.
• Interest in contributing to national and international initiatives shaping the future of computational pathology.

Compensation and Benefits

Pay range: $269,000 – $321,000 (annual). Compensation may be adjusted based on academic appointment, work experience, specialty training, geography, productivity, FTE basis, and role expectations. Eligible for performance‑based incentives. Benefits include health, dental, vision, life, and disability insurance, as well as a generous retirement plan with employer contributions.

Requisition Information

Requisition Number: R1619

EEO Statement

HMFP is an equal opportunity employer. HMFP respects diversity and does not discriminate on the basis of race, traits historically associated with race, including but not limited to hair texture, hair type, hair length, protective hairstyles, color, creed, religion, national origin, ancestry, citizenship status, age, disability, pregnancy (including pregnancy, childbirth, medical conditions related to pregnancy and childbirth, and breastfeeding), sex, gender, marital status, sexual orientation, gender identity or expression, veteran status, genetic information, or any other characteristic protected under applicable federal, state, or local laws.