NATIONAL UNIVERSITY OF SINGAPORE

Senior Research Fellow, Mathematical Modelling

Location
Singapore
Posted
08 Sep 2022
End of advertisement period
08 Oct 2022
Ref
10521744
Contract Type
Fixed Term
Hours
Full Time

Job Description

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

Senior Research Fellow (2 years minimum, possibility of extension)

Senior Research Fellow positions 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 researcher 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 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 and dengue vaccination modelling and modelling transmission and immunity using a range of serological datasets. There will be the opportunity to define and pursue independent research questions of mutual interest.

Major duties and responsibilities include:

  • undertaking literature reviews,
  • 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, and other supporting documents during the application.

For further enquiries, please contact Dr Hannah Clapham at hannah.clapham@nus.edu.sg

We regret that only shortlisted candidates will be notified.

Qualifications

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

Covid-19 Message

At NUS, the health and safety of our staff and students are one of our utmost priorities, and COVID-vaccination supports our commitment to ensure the safety of our community and to make NUS as safe and welcoming as possible. Many of our roles require a significant amount of physical interactions with students/staff/public members. Even for job roles that may be performed remotely, there will be instances where on-campus presence is required.

Taking into consideration the health and well-being of our staff and students and to better protect everyone in the campus, applicants are strongly encouraged to have themselves fully COVID-19 vaccinated to secure successful employment with NUS.