Postdoctoral Fellowship – AI and Machine Learning for Infectious Disease Modeling

Emory University • Atlanta, GA

13d • Onsite

About The Position

The Lau Lab in Emory University's Department of Biostatistics and Bioinformatics seeks 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 statistical, mathematical, computational, and machine learning methods—particularly deep learning and modern AI approaches—to improve 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 grounded in public health applications such as 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 methodological and applied publications.

The postdoctoral fellow will design and conduct research while receiving advanced training from a Principal Investigator to develop professional skills and research independence. The role includes designing and evaluating experiments, developing ideas that advance current research, and preparing and publishing scientific manuscripts under the direction of the Principal Investigator. The fellow may operate specific equipment, teach techniques, and train or supervise research staff.

The fellow will work closely with Dr. Max Lau in a collaborative, interdisciplinary environment spanning biostatistics, epidemiology, computer science, and infectious disease dynamics, with opportunities to collaborate with researchers in Computer Science, Epidemiology, and Biology at Emory. Professional development support includes conference travel, interdisciplinary collaborations, development of independent research programs, and publication in leading journals. The preferred start date is Spring–Summer 2027, with flexible timing for an exceptional candidate. The initial appointment is one year, with renewal expected based on satisfactory progress, mutual fit, and available funding; appointments may not exceed five years.

Requirements

• Doctoral degree or equivalent (such as Ph.D., M.D., Sc.D., D.V.M., or D.D.S.) in an appropriate field.
• Excellent scientific writing ability.
• Strong oral communication skills.
• Ability to work effectively and collegially with colleagues.

Nice To Haves

• Ph.D. 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 or mathematical modeling, machine learning, or computational methods.
• Experience with deep learning, probabilistic modeling, scientific machine learning, or related modern AI methods.
• 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.

Responsibilities

• Design and conduct research in statistical modeling, artificial intelligence, machine learning, and infectious disease epidemiology.
• Develop and apply statistical, mathematical, computational, and machine learning methods to study infectious disease dynamics.
• Design and evaluate experiments.
• Develop new ideas that promote current research and pursue independent research directions.
• Prepare and publish scientific manuscripts under the direction of the Principal Investigator.
• Contribute to research addressing epidemic forecasting, simulation-based inference, generative and foundation models, phylodynamics, and heterogeneous surveillance data.
• May operate specific equipment.
• May teach techniques to others and train or supervise research staff.

Benefits

• Professional development support, including conference travel.
• Opportunities for interdisciplinary collaborations.
• Support for developing an independent research program.
• Opportunities to publish in leading methodological and scientific journals.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Ph.D. or professional degree