Research Associate (Quantitative)

Interested applicants are invited to apply directly at the .

Your application will be processed only if you apply via .

We regret that only shortlisted candidates will be notified.

Job Description

Applications are invited for the following full-time position in the Saw Swee Hock School of Public Health:

Research Associate

We are looking for research associate with a quantitative background for ongoing research in Public Health.

The successful candidate will be working within the team under the Principal Investigator Assistant Professor Akira Endo, collaborating closely with multiple experts.

Methods include renewal process, network transmission modelling, and Bayesian inference, particularly in the context of epidemiology and dynamics of respiratory, sexually transmitted, and tick-borne infections.

Candidates should have a solid understanding of infectious disease dynamic modelling and statistical modelling, with a sufficient background in epidemiology, mathematics, and data science. Proficiency in R programming is essential, and we will also appreciate candidates with extensive coding knowledge of C++, Python, or Julia.

The candidate will be working with the Principal Investigator(s) on the analysis of predicting future trajectories of epidemics and assessing the potential impacts of response strategies using a range of modelling frameworks, including mathematical, statistical, and machine-learning approaches.

The Principal Investigator(s) is seeking an independent worker who is well-organised, analytical and codes competently. They will, however, be receiving support from a team of mathematicians, epidemiologists and statisticians, and have a diverse portfolio of tasks. Under the team's guidance, they will be expected to co-lead their own publications.

We welcome academic creativity and will be highly supportive of candidates who wish to either pursue academia or desire for career progression provided they show self-motivation to showcase their problem-solving abilities.

Responsibilities:

. Infectious disease modelling

. Statistical analyses

. Stochastic processes

. Academic writing and publication of results

. Preparation of meeting materials for stakeholders

Requirements:

. Completed an MSc in a quantitative discipline(statistics, mathematics, computational biology, data science)

. Extensive experience in public health research and experience in leading at least one quantitative research project

. At least one (preferably more) academic publication as a main author (first/corresponding/last) in disciplines relevant to public health (preferably with a focus on infectious disease modelling)

. Strong programming skills (at least one of R/Python/Julia)

. Statistical competence (understands and can perform likelihood-based inference, ideally including Bayesian)

Please email the PI at for further details.