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ViceChairforResearch|Director,EmergencyMedicineInformaticsUniversityofMarylandSchoolofMedicine|UniversityofMarylandInstituteforHealthComputingPositionOverview

The Department of Emergency Medicine at the University of Maryland School of Medicine (UMSOM), in partnership with the University of Maryland Institute for Health Computing (UM-IHC), invites applications for a tenured or tenure-track faculty position at the rank of Associate Professor or Full Professor. The successful candidate will serve as Vice Chair for Research in the Department of Emergency Medicine and hold a joint appointment at UM-IHC as Director of Emergency Medicine Informatics, providing strategic and scientific leadership at the intersection of emergency medicine and health data science.

The following is an exceptional opportunity for a clinician-scientist with a strong foundation in biomedical informatics, clinical artificial intelligence, or health data science to build and lead a nationally recognized research program, shape the informatics infrastructure of real-world emergency care settings, and mentor the next generation of physician-informaticists.

Key Responsibilities DepartmentalLeadership(ViceChairforResearch)

• Serve as Vice Chair for Research in the Department of Emergency Medicine, providing strategic oversight of the department's research portfolio, mentoring faculty in grant development, and representing the department on institutional research committees.
• Work collaboratively with the Department Chair to develop and execute a departmental research strategic plan, recruit research-oriented faculty, and build the infrastructure necessary to support a thriving academic research enterprise.
• Oversee departmental research operations including coordination with sponsored programs, IRB compliance, and research administration.

Informatics Leadership (Director Role at UM-IHC)

• Serve as the strategic and scientific Director of Emergency Medicine Informatics within UM-IHC, setting the research agenda and overseeing related programs and personnel.
• Lead the design, implementation, and evaluation of clinical decision support tools, predictive models, and AI/ML-enabled workflows within the emergency department.
• Partner with the Department’s Center for EM Data Analytics and Reporting (CEDAR), informatics, data engineering, and IT teams to optimize EHR-integrated clinical workflows and ensure high-quality data capture for research and quality improvement.
• Partner with CEDAR to develop and oversee emergency medicine data assets, including clinical registries, real-world data pipelines, and federated data networks.
• Establish and maintain collaborative relationships with industry, government agencies, and other academic medical centers to advance the field.
• Represent emergency medicine informatics interests on UM-IHC governance bodies, UMSOM committees, and external advisory boards.

Research & Scholarship

• Develop and maintain a funded, independent research program in emergency medicine, with a focus on informatics areas such as clinical AI/ML, natural language processing of clinical text, predictive analytics, clinical decision support, or large language model applications in acute care.
• Seek and successfully compete for extramural funding from the NIH, AHRQ, PCORI, NSF, foundations, and/or industry sponsors.
• Produce high-impact peer-reviewed publications and present findings at national and international conferences.
• Collaborate across departments and schools on multi-disciplinary research initiatives involving clinical informatics, biostatistics, population health, and health services research.
• Contribute to and lead multi-site research consortia and learning health system initiatives.

• Maintain board-certified clinical practice in emergency medicine, with shifts commensurate with academic appointment and research productivity.
• Contribute clinical expertise to the design and testing of informatics tools and AI-enabled interventions in real-world emergency care settings.

Education & Mentorship

• Mentor medical students, residents, fellows, and junior faculty interested in clinical informatics, AI, and data science.
• Contribute to curriculum development in health informatics, data science, and evidence-based medicine across graduate medical education and fellowship programs.
• Participate in teaching activities within the School of Medicine and, as appropriate, affiliated schools of public health, nursing, and pharmacy.

Required Qualifications

• M.D., D.O., or M.D./Ph.D. (or equivalent terminal degree) with board certification or board eligibility in Emergency Medicine.
• Eligibility for medical licensure in Maryland.
• Demonstrated record of peer-reviewed publications and extramural funding commensurate with appointment at the Associate Professor or Full Professor level.
• Substantial expertise in at least one of the following: artificial intelligence, machine learning, clinical decision support systems, EHR data science, learning health systems.
• Experience with large-scale clinical data analysis, including structured and unstructured EHR data, administrative claims, or other real-world data sources.
• Evidence of leadership in informatics, data science, or a related field (e.g., program leadership, center directorship, or national committee work).
• Strong written and oral communication skills and a collaborative approach to interdisciplinary research.

Preferred Qualifications

• Formal training in biomedical informatics, clinical data science, or a related field.
• Subspecialty certification in clinical informatics.
• Active NIH or AHRQ funding as principal investigator.
• Experience with federated learning, privacy-preserving data analysis, or multi-site clinical data networks (e.g., PCORnet, CTSA consortium, USCDI).
• Familiarity with regulatory and ethical frameworks for AI in clinical settings, including FDA guidance on SaMD and algorithmic bias mitigation.
• Track record of successful translational informatics projects from research to clinical implementation.
• Experience mentoring individuals from underrepresented groups in medicine and data science.