Research fellow position(s) are available in the Saw Swee Hock School of Public Health to
join the team of the Principal Investigator, Assistant Professor Hannah Clapham. The
research team is newly established and growing and collaborates with other research
groups with SSHSPH and internationally. The team works on modelling of infectious
diseases for public health policy in Singapore and across Asia. See more details here:
blog.nus.edu.sg/clapham/
The researchers will have the chance to work on one or more of a number of research projects using
mathematical modelling to understand dynamics and optimal control of infectious diseases
in Singapore and in Asia. Projects include modelling Japanese Encephalitis burden,
modelling of dengue and COVID-19 transmission and vaccination and control strategies.
There will be the opportunity to define and pursue independent research questions of
mutual interest.
Major duties and responsibilities include:

• leading on analysing data using statistical and mathematical modelling techniques,
• leading on writing reports, presentations, and publication of results and findings in
  peer-reviewed journal,
• generating research questions,
• assisting the PI with supervision of junior team members
• collaborating with researchers in other national and international institutions
  The candidate must:
• possess EITHER a PhD with topic covering mathematical modelling of biological
  systems or infectious disease epidemiology or related field OR PhD in computational
  or statistical field with an interest in the application of quantitative methods to
  epidemiology and public health questions
• be an independent worker who is well- organized and has an eye for detail.
• possess excellent written and verbal communication skills,
• possess the ability to work effectively and lead teams of colleagues within and across
  organisations and from different disciplines,
• 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 experience of inter-disciplinary collaborations

The grade of appointment will be based on candidate’s academic qualifications and years of
relevant experience.

Recruitment is open immediately, and will continue until the position is filled. Applicants
should send a brief statement of interest, CV, three named references, NUS Personal Data
Consent for Job Applicants: http://www.nus.edu.sg/careers/potentialhires/applicationprocess/NUS-Personal-Data-Consent-for-Job-Applicants.pdf and other supporting documents to with email subject
“RF for modelling” to Dr Hannah Clapham, hannah.clapham@nus.edu.sg