Emory University is a leading research university that fosters excellence and attracts world-class talent to innovate today and prepare leaders for the future. We welcome candidates who can contribute to the excellence of our academic community.

The Lau Lab in the Department of Biostatistics and Bioinformatics at Emory University is seeking a highly motivated postdoctoral fellow to conduct research at the intersection of statistical modeling, artificial intelligence, machine learning, and infectious disease epidemiology.

The fellow will develop and apply novel statistical, mathematical, computational, and machine learning methods, with particular emphasis on deep learning and modern AI approaches, to improve our understanding, inference, and prediction of infectious disease dynamics. Potential research areas include epidemic forecasting,deep learning–based simulation-based inference, generative and foundation models for epidemiology, phylodynamics, and integration of heterogeneous surveillance
data.

Projects are strongly grounded in real-world public health applications, including pandemic preparedness, outbreak forecasting, infectious disease surveillance, and data-driven public health decision-making. The fellow will have substantial opportunities to develop independent research directions and lead high-impact methodological and applied publications.

Position Details
• Start date: Spring-Summer 2027 preferred; timing is flexible for an exceptional candidate
• Initial term: 1 year, with the expectation of renewal based on performance, mutual fit, and funding
• Location: Emory University, Atlanta, Georgia

JOB DESCRIPTION: Helps design and conduct research within a specified field while receiving advanced training from a designated Principal Investigator to enhance professional skills and research independence needed for pursuit of a career. The specific area of research in which the trainee is mentored is determined by the department and laboratory of the Postdoc. Designs and evaluates experiments. Develops new ideas that promote current research. Prepares and publishes scientific manuscripts under the direction of the Principal Investigator. May be responsible for operation of specific equipment. May teach techniques to others, train, and supervise research staff. Positions are temporary appointments as a research trainee. The initial appointment is for one year, renewal expected if progress is satisfactory and funds are available. Appointments cannot exceed five years.

MINIMUM QUALIFICATIONS: A doctoral degree or equivalent (Ph.D., M.D., ScD., D.V.M., DDS etc) in an appropriate field. Excellent scientific writing ability and strong oral communication skills. The ability to work effectively and collegially with colleagues. Additional qualifications as specified by the Principal Investigator.

Preferred Qualifications

• PhD in statistics, biostatistics, computer science, applied mathematics, physics, artificial intelligence, or another closely related quantitative field
• Strong interest in applying quantitative and computational methods to infectious disease epidemiology
• Strong background in statistical/mathematical modeling, machine learning, or computational methods
• Experience with deep learning, probabilistic modeling, scientific machine learning, or related modern AI methods is particularly desirable
• Strong interest in interdisciplinary research
• Proficiency in Python and R; experience with additional scientific computing frameworks is desirable
• Strong research record and evidence of growing independence.
• Strong written and verbal communication skills

Candidates are not expected to have prior experience in every area listed above. Applicants with particularly strong methodological or computational backgrounds who are genuinely interested in applying their expertise to infectious disease problems are encouraged to apply.

Research Environment
The Lau Lab provides a highly collaborative and interdisciplinary research environment spanning biostatistics, epidemiology, computer science, and infectious disease dynamics. The fellow will work closely with Dr. Max Lau and will have opportunities to collaborate with leading researchers at Emory from Computer Science, Epidemiology and Biology. Postdoctoral fellows will receive strong support for professional development, including conference travel, interdisciplinary collaborations, development of independent research programs, and publication in leading methodological and scientific journals.

Application Instructions
Interested applicants should apply through the Emory portal.

Please include:
• Curriculum vitae (CV)
• Statement of research interests
• Contact information for two references. Reference letters will be requested from candidates selected for interview.

Questions may be directed to Dr. Max Lau at msy.lau@emory.edu.
Review of applications will begin immediately and continue until the position is filled.

Emory is an equal opportunity employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by state or federal law. Emory University does not discriminate in admissions, educational programs, or employment, including recruitment, hiring, promotions, transfers, discipline, terminations, wage and salary administration, benefits, and training. Students, faculty, and staff are assured of participation in university programs and in the use of facilities without such discrimination. Emory University complies with Section 503 of the Rehabilitation Act of 1973, the Vietnam Era Veteran's Readjustment Assistance Act, and applicable executive orders, federal and state regulations regarding nondiscrimination, equal opportunity, and affirmative action (for protected veterans and individuals with disabilities). Inquiries regarding this policy should be directed to the Emory University Department of Equity and Civil Rights Compliance, 201 Dowman Drive, Administration Building, Atlanta, GA 30322. Telephone: 404-727-9867 (V) | 404-712-2049 (TDD).

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