Research Associates/Research Assistants are required for concurrent research projects in the laboratory of Assistant Professor Lim Jue Tao.
This project, led by the Lee Kong Chian School of Medicine (LKCMed), Nanyang Technological University, will be conducted in collaboration with the Saw Swee Hock School of Public Health (SSHSPH), National University of Singapore, the Environmental Health Institute, National Environment Agency, Singapore and the French National Centre for Scientific Research. This position will offer a multidisciplinary and unique collaborative environment with diverse learning opportunities. The successful applicant(s) will work as part of a growing and energetic team investigating health at the interface of environment, climate change and infectious diseases in local and international contexts. The successful candidates will work together with the PI to develop models to understand the risk factors leading to increased burden of environmental infectious diseases across large spatial scales.
This position is based in Clinical Sciences Building, Nanyang Technological University.
Key Responsibilities:
- Develop models to understand the transmissibility of infectious diseases
- Develop models to understand the medium to long-term burden of infectious diseases across different spatial scales
- Undertaking literature reviews
- Leading on analysing data using statistical and data science techniques
- Leading on writing reports, presentations, and publication of results and findings in peer-reviewed journal
- Generating research questions
- Collaborating with researchers in other national and international institution
Competencies and Qualification Requirements:
- Masters (Research Associate), Bachelors (Research Assistant), or equivalent in a related discipline. i.e statistics/epidemiology/data science. Post-graduate qualifications in other quantitative disciplines are welcome to apply.
- Background and research experience in epidemiology
- A strong interest in infectious diseases, spatial statistics and health data science
- Ability to communicate findings effectively
- Ability to work in a diverse and large team of researchers
- Well-organized and has an eye for detail
- Possess good written and verbal communication skills
- Possess the ability to work effectively in teams
- Have good proficiency in Statistical software (R)
It would be desirable for the candidate to:
- Have good proficiency in other programming languages, for example Python/C/C++
- Have a strong interest in learning quantitative skills
