Population Health Discipline – Gilbert and Rose-Marie Chagoury School of Medicine
Employment Type: Full-time Faculty
Location: Byblos Campus
Position Overview
The Gilbert and Rose-Marie Chagoury School of Medicine at the Lebanese American University invites applications for a full-time faculty position at the Assistant Professor, Associate Professor, or Professor level in Health Data Science, within the Population Health Discipline. We seek a highly qualified and collaborative academic with expertise in health data science and advanced analytics and a strong interest in applying computational and data-driven approaches to healthcare data, electronic health records, population health, health systems research and clinical research.
The position is intended to complement existing expertise in epidemiology and biostatistics by strengthening the School’s capabilities in health data integration, predictive modeling, digital health technologies, and data-driven healthcare innovation. The successful candidate will develop an impactful research portfolio, contribute to undergraduate and graduate medical education, support interdisciplinary research and academic program development, and collaborate closely with the School’s Digital Health and Artificial Intelligence program.
Key Responsibilities
The successful candidate will be expected to:
- Contribute to teaching within the Population Health Discipline in medical, and health professions programs.
- Develop and deliver educational content in population health data science, data visualization, and related quantitative methods, and machine learning in coordination with the School's Digital Health and AI curriculum.
- Contribute to curriculum development, educational innovation, assessment, and continuous quality improvement.
- Develop and maintain an independent and externally visible research program appropriate to academic rank in population health data science.
- Lead and collaborate on interdisciplinary research using real-world health and healthcare data, including electronic health records, registries, administrative databases, population-health datasets, environmental and spatial data, and other complex data sources.
- Apply advanced data-science approaches to the analysis, interpretation, visualization, and translation of health data.
- Collaborate with epidemiologists, biostatisticians, clinicians, public health researchers, and other faculty to strengthen the methodological and analytical capabilities of multidisciplinary research teams.
- Pursue competitive internal and external research funding and contribute to high-quality peer-reviewed scholarship.
- Supervise and mentor medical students, graduate students, residents, fellows, research staff, and junior investigators, as appropriate.
- Contribute to health data-analytics resources and initiatives, in coordination with existing digital health and AI structures within the School of Medicine and its affiliated medical centers.
- Participate in the design, development, coordination, and leadership of academic programs, concentrations, certificates, courses, or other educational initiatives related to health data science.
- Participate actively in academic service, including discipline, School, and University committees and other institutional initiatives.
- Contribute to professional, community, and external partnerships that advance the School's academic and research mission.
Required Qualifications
Candidates should hold a PhD or equivalent doctoral degree in Health Data Science, Biomedical Data Science, Biomedical Informatics, Health Informatics or a closely related field, with a demonstrated record of applying data-science and computational methods to health, healthcare, clinical, or population-health questions.
Candidates should demonstrate:
- A strong record of research and scholarly productivity appropriate to the proposed academic rank.
- Strong expertise in health data science and advanced data analytics.
- Expertise in population health informatics and digital health, including experience with electronic health records, health information systems, clinical and public health databases, and interoperability.
- Expertise in health data management and integration, including data acquisition, cleaning, transformation, integration of heterogeneous data sources, database management, data quality assessment, and reproducible analytical workflows.
- Proficiency in relevant programming and analytical tools, particularly R and /or Python and visualization or business-intelligence platforms such as Power BI or comparable tools.
- Experience applying advanced statistical modeling and machine-learning techniques, including predictive analytics and risk modeling, to healthcare, clinical, and population health data.
- Experience working with real-world and complex health datasets, such as electronic health records, registries, administrative or claims data, public health surveillance data, population-health datasets, or other routinely collected healthcare data.
- Evidence of effectiveness or strong potential in university-level teaching and mentorship.
- Ability to work effectively in multidisciplinary and interdisciplinary teams.
- Excellent written and oral communication skills in English.
Areas of Additional Expertise
Expertise in one or more of the following areas would be particularly valuable:
- Advanced and emerging Health Data Science methods, including natural language processing, predictive analytics, large-scale and longitudinal health data analysis, multimodal data integration, and other computational approaches relevant to health and medicine.
- Public health intelligence and surveillance, including population health monitoring, automated and digital surveillance, early-warning systems, and data-driven decision-support tools.
- Geographic Information Systems (GIS) and spatial epidemiology, including health data mapping and spatial or spatiotemporal analysis of population, environmental, and clinical data.
- Health data governance and responsible data use, including privacy, security, ethics, and equity considerations.
- Competitive research funding and academic leadership, including a demonstrated track record of securing research grants and leading interdisciplinary research initiatives.
Application Requirements
Applicants should submit:
- A cover letter describing their interest in the position and relevant qualifications.
- A detailed curriculum vitae.
- A statement of teaching philosophy and educational experience.
- A statement outlining current and future research interests.
- Copies or links to selected representative publications.
- Names and contact information of three professional references.
Applications should be submitted via email to Dean Sola Aoun Bahous sola.bahous@lau.edu.lb with a copy to roula.faour@lau.edu.lb
Application Deadline: Applications will be accepted until the position is filled.
For additional information, please contact Mrs. Roula Faour, Senior Faculty Affairs Associate, Office of the Dean, at roula.faour@lau.edu.lb