Project: This project seeks to transform our understanding of infectious disease transmission by integrating large-scale digital contact tracing data with detailed clinical and virological records. The student will develop cutting-edge statistical and mechanistic models to bridge within-host viral dynamics and between-host transmission processes, enabling precise inference of time-varying infectiousness and individual-level transmission risk. Leveraging uniquely rich real-world datasets, the work will generate a unified, data-driven framework for transmission biology. The project has direct implications for next-generation public health strategies, including optimized isolation, testing, and contact tracing policies, while providing rigorous training at the frontier of epidemiology, data science, and computational modeling.

Program and Place of Work: This project will support 1 graduate student (PhD level) in the Lee Kong Chian School of Medicine at the Nanyang Technological University graduate program. The graduate students will be based at Clinical Sciences Building, Lee Kong Chian School of Medicine, Nanyang Technological University. The successful applicant(s) will work as part of a growing and energetic team, focusing on quantitatively understanding biological mechanisms of infection and its impact on both individual and population health. Particularly, we have been working to understand the viral dynamics at individual level and how it is associated with population level epidemiological dynamics. Using mathematical modelling and computer simulation as core approaches, we will connect basic biological mechanism of infection and infectious disease epidemiology and clinical studies, which would accelerate vaccine, drugs, and treatment development and provide a more comprehensive picture of the mechanisms behind the dynamics of infectious diseases.

Qualifications: Candidates should have a MSc degree in a quantitative field, such as data science, computational biology, mathematics, computer science, (bio)statistics, or related field. Research experience and/or educational background on public health and medicine is a plus but not essential. Candidate with bachelor’s degree in the above disciplines with strong record of research will be considered. The candidate should have strong quantitative skills, or at least demonstrate interest in developing skills in statistics and infectious disease modelling. The successful candidate will have a strong aptitude for communication and teamwork and have demonstrated good academic performance in their past programs.

Support: fully funded for 3 years, with monthly stipend, tuition fees and conference funding. For outstanding students, internal top-up award opportunities are available on a competitive basis.

Start Date: The positions will start in January 2027 at the earliest. Application deadline for LKCMed PhD program and admission requirements can be found here: https://www.ntu.edu.sg/education/graduate-programme/lkcmedicine-phd-by-research-programme.

Application: Interested candidates should send by email a current curriculum vitae, a scanned copy of transcript. Application reviews are on-going, so apply as soon as you can.

For further information about the above research opportunities, please contact Dr. Keisuke Ejima (LKCMed) keisuke.ejima [at] ntu.edu.sg.

​There are two intakes each year - August and January. Please apply before the closing date for the preferred intake:
Admission Intake: Application Period
August: 1 November - 31 December
January: 1 May - 30 June