Faculty Position in Health Data Science

About the role

The Gilbert and Rose-Marie Chagoury School of Medicine at the Lebanese American University is seeking a full-time faculty member at Assistant Professor, Associate Professor or Professor level in Health Data Science within the Population Health Discipline. The position strengthens the School's capabilities in health data integration, predictive modeling, digital health technologies and data-driven healthcare innovation, complementing existing expertise in epidemiology and biostatistics. It sits alongside the School's Digital Health and Artificial Intelligence program.

Key responsibilities

• Teach in the Population Health Discipline and deliver content in population health data science, data visualization, quantitative methods and machine learning, coordinating with the Digital Health and AI curriculum.
• Develop and maintain an independent research program and lead interdisciplinary research using real-world health data such as electronic health records, registries, administrative databases and environmental and spatial data.
• Pursue research funding, publish peer-reviewed work and supervise students, residents, fellows and junior investigators.
• Contribute to curriculum development, assessment, quality improvement and academic programs, and take part in academic service and external partnerships.

Required profile

• PhD or equivalent in Health Data Science, Biomedical Data Science, Biomedical Informatics, Health Informatics or a closely related field.
• Strong record of research and scholarly productivity appropriate to the proposed rank.
• Evidence of effectiveness or strong potential in university-level teaching and mentorship.
• Ability to work in multidisciplinary teams and excellent written and oral English.

Required skills

• Health data science and advanced analytics, including population health informatics and digital health.
• Data management and integration, including data cleaning, transformation, database management and reproducible workflows.
• Programming in R and/or Python, and visualization or business-intelligence tools such as Power BI.
• Statistical modeling and machine learning, including predictive analytics and risk modeling.
• Experience with EHRs, registries, claims data and public health surveillance data.

Applications include a cover letter, CV, teaching and research statements, publication list and three references, sent by email to the Dean's office; applications are accepted until the position is filled.