Research Fellow (Infectious Disease Modelling, Phylogeny, and Machine Learning for Public Health)

Updated: 5 months ago
Job Type: FullTime
Deadline: 08 Jun 2023

10 May 2023
Job Information

Research Field

Biological sciences
Computer science
Medical sciences
Researcher Profile

First Stage Researcher (R1)

Application Deadline

8 Jun 2023 - 00:00 (UTC)
Type of Contract

Job Status

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme
Is the Job related to staff position within a Research Infrastructure?


Offer Description

Job Description

Saw Swee School of Public Health at the National University of Singapore (NUS) seeks a highly motivated and skilled Research Fellow to join our interdisciplinary team. This position offers the opportunity to work on groundbreaking research projects in the broad areas of infectious disease modelling, phylogeny, phylodynamics, machine learning for public health, and global health. The work will allow you to collaborate with a broad spectrum of people at school ( ), Institute of Data Science ( ), and global leaders who are part of the ‘Machine Learning & Global Health’ network ( ). You can find more information about the work done by Asst. Prof Swapnil Mishra by looking here

Key Responsibilities:

  • Conduct high-quality research in infectious disease modelling, phylogenetics, phylodynamics, and/or machine learning applied to public health and global health.
  • Develop and implement computational models, statistical methods, and machine learning algorithms to analyze infectious disease data.
  • Collaborate with multidisciplinary teams of researchers, including epidemiologists, biologists, machine learners, biostatisticians, and public health experts.
  • Analyze large-scale datasets to generate insights into the transmission dynamics, evolution, and control of infectious diseases.
  • Present research findings at national and international conferences and publish results in peer-reviewed scientific journals.
  • Assist in the supervision and mentoring of graduate students and junior researchers.
  • Contribute to grant proposals and progress reports for funding agencies.


  • A Ph.D. in a relevant field such as computer science, statistics, epidemiology, computational biology, bioinformatics, biostatistics, machine learning, or a related discipline.
  • Strong background in any one of machine learning, generative modelling, infectious disease modelling, phylogenetics, and phylodynamics.
  • Proficiency in programming languages such as R, Python, C++, or Julia.
  • Experience with machine learning and statistical methods applied to real-world, public health, and global health problems.
  • Excellent written and verbal communication skills, including presenting complex concepts to diverse audiences.
  • Demonstrated ability to work effectively in a multidisciplinary team and independently.
  • Track record of publications in peer-reviewed journals.

Application Process:

Interested applicants should submit the following documents:

  • A cover letter explaining your interest in the position, relevant experience, and research interests.
  • A detailed curriculum vitae, including a list of publications.
  • A brief research statement (maximum 2 pages) outlining your research experience and future plans.
  • Contact information for three professional references who can provide letters of recommendation upon request.

Review of applications will begin immediately and continue until the position is filled. The anticipated start date is July 2023, but this is negotiable. The initial appointment will be for one year, with the possibility of renewal based on performance.

NUS is an equal-opportunity employer committed to diversity and inclusion. We welcome applications from all qualified individuals, regardless of race, color, religion, gender, sexual orientation, age, national origin, or disability.

In case of any questions or queries, please do not hesitate to contact Ass. Prof Swapnil Mishra with the subject line ‘Research Fellow in Infectious Disease Modelling, Phylogeny, and Machine Learning for Public Health’.


A Ph.D. in a relevant field such as computer science, statistics, epidemiology, computational biology, bioinformatics, biostatistics, machine learning, or a related discipline.

Contact list for further enquiries

Hiring Manager: [[Assistant Prof Swapnil Mishra]]
Hiring Manager Email: [[ ]]

Additional Information
Where to apply

View or Apply

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