Research Associate/Assistant in Infectious Disease Modelling and Machine Learning for Public Health
Salary: Commensurate with experience
The National University of Singapore's Saw Swee School of Public Health (NUS) seeks a dedicated and skilled research associate (assistant) to join its multidisciplinary team. This position offers a unique opportunity to participate in innovative research projects on various topics such as infectious disease modelling, phylogeny, and characterizing human mobility patterns. The project allows you to collaborate with school personnel (sph.nus.edu.sg/research), the Institute of Data Science (ids.nus.edu.sg/), and global leaders (mlgh.net/). More information about Swapnil Mishra can be found here: https://smishra.dev/
- Conduct high-quality research in infectious disease modelling, human mobility patterns, 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 human mobility patterns using survey, mobile or social media data.
- Present research findings at national and international conferences and publish results in peer-reviewed scientific journals.
- Assist in the supervision and mentoring of junior researchers.
- Contribute to grant proposals and progress reports for funding agencies.
- Solid background in Bayesian inference, statistical modelling, and graph networks.
- Proficiency in programming languages such as R or Python.
- Prior experience in working with Stan or PyMC or NumPyro or Turing, or any other probabilistic programming language.
- Excellent written and verbal communication skills, including presenting complex concepts to diverse audiences.
- Demonstrated ability to work independently and as part of a multidisciplinary team.
- A history of publications in peer-reviewed journals is preferred.
Interested applicants should submit the following documents during the application:
- A cover letter explaining your interest in the position, relevant experience, and research interests.
- A comprehensive curriculum vitae, including a list of publications (if applicable).
- A brief research statement (maximum two pages) outlining your research experience and future aspirations.
- Contact information for two 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 December 2023, but this is negotiable. The initial appointment will be for one year, with the possibility of renewal based on performance and funding availability. There will be an opportunity to pursue PhD at NUS if interested.
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 at ‘email@example.com’ with the subject line ‘Research Associate/Assistant in Infectious Disease Modelling, and Machine Learning for Public Health’.
A Master’s. in a relevant field such as computer science, statistics, epidemiology, computational biology, bioinformatics, biostatistics, machine learning, or a related discipline.
Location: Kent Ridge Campus
Organization: Saw Swee Hock School of Public Health
Department : Saw Swee Hock School of Public Health
Employee Referral Eligible: No
Job requisition ID : 22519
Contact list for further enquiries
Hiring Manager: [[Assistant Professor Swapnil Mishra]]
Hiring Manager Email: [[firstname.lastname@example.org]]