Job Description

Saw Swee School of Public Health at the National University of Singapore (NUS) is currently seeking a dedicated and skilled Research Assistant to join our interdisciplinary team. This position offers a unique opportunity to engage in innovative research projects across a range of topics, including 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 (https://sph.nus.edu.sg/research/), 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 https://smishra.dev/

Key Responsibilities:

• Assisting high-quality research in infectious disease modelling, phylogenetics, phylodynamics, and/or machine learning applied to public health and global health.
• Support the development and implementation of 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.
• Help analyze large-scale datasets to generate insights into the transmission dynamics, evolution, and control of infectious diseases.
• Participate in the preparation and presentation of research findings at conferences and in peer-reviewed scientific journals.
• Assist with administrative tasks and grant proposal preparation.

Qualifications:

• An undergraduate degree in a relevant field such as computer science, statistics, epidemiology, computational biology, bioinformatics, biostatistics, machine learning, or a related discipline.
• A basic understanding of any one of machine learning, generative modelling, infectious disease modelling, phylogenetics, and phylodynamics.
• Some experience with programming languages such as R, Python, C++, or Julia.
• Interest in machine learning and statistical methods applied to public health and global health problems.
• Interested to work both independently and as part of a multidisciplinary team.
• Strong written and verbal communication skills, with the ability to present complex concepts to diverse audiences.

Application Process:
Interested applicants should submit the following documents:

• 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 2 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 July 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 with the subject line Research Assistant in Infectious Disease Modelling, Phylogeny, and Machine Learning for Public Health.

Qualifications

An undergraduate degree 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: [[ ]]

Times Higher Education