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Research Fellow

4 weeks ago

Singapore NATIONAL UNIVERSITY OF SINGAPORE Full time
Roles & Responsibilities

Interested applicants are invited to apply directly at the NUS Career Portal

Your application will be processed only if you apply via NUS Career Portal

We regret that only shortlisted candidates will be notified.

Job Description

Job Title: Research Fellow in Infectious Disease Modelling for Dengue & Zika Genomic Epidemiology and Surveillance

About the Role:

Saw Swee School of Public Health at the National University of Singapore (NUS) is looking for a highly motivated Research Fellow to join our interdisciplinary team. You'll be working on a cutting-edge program involving a +10-country arbovirus genomic surveillance initiative focused on dengue and Zika viruses. This project is a collaboration between research institutions and Ministries of Health across Asia , building upon the existing UNITEDengue (https://www.unitedengue.org/). You will be responsible for developing toolkits for real-time surveillance of genomic data by integrating climate and mosquito vector factors to support environmental and public health responses.

Collaborating Team

● Environmental Health Institute (EHI), National Environmental Agency (NEA), Singapore: Prof. Ng Lee Ching, Dr. Tan Cheong Huat, Dr. Judith Wong, and Dr. Chanditha Hapuarachchi.

● Pathogen Genomic Epidemiology Unit, MRC Global Infectious Disease Analysis, Imperial College London (ICL): Prof. Nuno R. Faria, Dr. Oliver Ratmann, Dr. Charlie Whittaker, and Dr. Kris Parag.

● Saw Swee Hock School of Public Health, National University Singapore (NUS): Dr. Swapnil Mishra.

● UNITEdDengue Partners

Key Responsibilities:

● Develop mathematical and statistical virus evolution models to:

a. Identify virus lineages with high epidemic potential

b. Track changes in adaptation and immune escape properties of viruses against vector control strategies like Wolbachia

● Develop real-time dashboards to track and share cross-border genomic and epidemiological data.

● Collaborate with the multidisciplinary team (EHI, ICL, NUS) of researchers, including epidemiologists, biologists, machine learners, biostatisticians, and public health experts.

● Analyse large-scale datasets to generate insights into the transmission dynamics, evolution, and control of arboviral 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.

Interested applicants should submit the following documents

● A cover letter explaining your interest in the position, relevant experience, and research interests.

● A detailed CV, 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 1st September 2025, but this is negotiable. The initial appointment will be for one year, with the possibility of renewal of up to 3 years 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 Asst. Prof Swapnil Mishra at 'swapnil dot mishra at nus dot edu dot sg' with the subject line as the Job Title.

Qualifications

● 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 at least one of infectious disease modelling, phylogenetics, or phylodynamics (background in computational statistics or machine learning is optional but highly relevant)

● Proficiency in programming languages (R, Python, C++, Java or Julia).

● Experience with mathematical 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

Tell employers what skills you have

Machine Learning
Epidemiology
Computer Science
Phylogenetics
Python
Bioinformatics
Statistics
Computational Biology
C++
Biostatistics