Postdoctoral Fellowship – AI and Machine Learning for Infectious Disease Modeling

Emory • Atlanta, GA

13d • Onsite

About The Position

The Lau Lab in Emory University's Department of Biostatistics and Bioinformatics is seeking a 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—especially deep learning and modern AI approaches—to improve understanding, inference, and prediction of infectious disease dynamics. Potential topics 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 opportunities to develop independent research directions and lead methodological and applied publications. In this research-trainee appointment, the fellow receives advanced training from a Principal Investigator, designs and evaluates experiments, develops research ideas, and prepares and publishes scientific manuscripts under the PI's direction. The fellow may operate equipment and may teach techniques, train, or supervise research staff. The Lau Lab is collaborative and interdisciplinary, spanning biostatistics, epidemiology, computer science, and infectious disease dynamics. The fellow will work closely with Dr. Max Lau and may collaborate with researchers in Computer Science, Epidemiology, and Biology at Emory.

The preferred start is Spring–Summer 2027, with flexible timing for an exceptional candidate. The initial appointment is one year, with renewal expected subject to satisfactory progress, mutual fit, and available funding; appointments may not exceed five years. The position is based at Emory University in Atlanta, Georgia. Applications are submitted through the Emory portal and should include a CV, a statement of research interests, and contact information for two references. Reference letters will be requested from candidates selected for interview. Review begins immediately and continues until the position is filled.

Requirements

• Doctoral degree or equivalent (such as Ph.D., M.D., ScD., D.V.M., or DDS) in an appropriate field.
• Excellent scientific writing ability.
• Strong oral communication skills.
• Ability to work effectively and collegially with colleagues.
• Additional qualifications as specified by the Principal Investigator.

Nice To Haves

• 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 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

• Conduct research in statistical modeling, artificial intelligence, machine learning, and infectious disease epidemiology.
• Develop and apply statistical, mathematical, computational, and machine-learning methods to understand, infer, and predict 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.
• Collaborate with researchers across biostatistics, epidemiology, computer science, and biology.
• May operate specific equipment.
• May teach techniques to others and train or supervise research staff.

Benefits

• Professional development support, including conference travel, interdisciplinary collaborations, development of independent research programs, and publication in leading methodological and scientific journals.

What This Job Offers

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