Public Health Data Scientist (Quant) – Disease Modeling

National University of Singapore; Kent (WA); On-site; USD 50,000 - 70,000; Full time

Job summary

National University of Singapore seeks a full-time Research Assistant for the Saw Swee Hock School of Public Health. The successful candidate will work on disease modelling and data analysis, utilizing statistical methods and programming skills, particularly in R.

The position involves collaboration with a diverse team, providing support for academic publications and data-driven research in public health. Candidates with a BSc in quantitative disciplines and strong programming skills are encouraged to apply.

Qualifications

• Completed a BSc in a quantitative discipline (statistics, mathematics, computational biology, data science).
• Strong programming skills (R preferred).
• Statistical competence (Bayesian is advantageous).

Responsibilities

• Conduct disease modelling.
• Perform statistical analyses.
• Engage in academic writing and publication of results.
• Prepare meeting materials for stakeholders.

Skills

Statistical modelling

R programming

C++ knowledge

Python knowledge

Education

BSc in a quantitative discipline

Job description

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

Research Assistant

We are looking for research assistants with a quantitative background for ongoing research in Public Health.

They will be working within the team under the Principal Investigator Assistant Professor Borame Dickens alongside multiple collaborators and experts.

Methods include agent based/individual based modelling, SEIR modelling, geospatial statistics, Bayesian statistics, burden mapping, measuring the impact of the environment on disease among others. The PI has projects in both infectious and chronic disease, measuring the impact of interventions.

Candidates need to be able to understand statistical modelling, have a mathematical background, and be fluent in R programming. We will also consider candidates who have extensive C++ or Python coding knowledge as these are transferrable to R.

The candidate will be working with the Principal Investigator(s) on the analysis of national health datasets, utilising an array of methods to infer statistical relationships and health outcomes. Further mathematical modelling will also be carried out when necessary involving diagnostic flows and where appropriate, disease spread and/or illness progression.

The Principal Investigator(s) is seeking for an independent worker who is well-organized, analytical and codes competently. They will however be receiving support from a team of mathematicians, epidemiologists and statisticians, and have a diverse portfolio of tasks. Under the team’s guidance, they will be expected to co-lead their own publications.

We welcome academic creativity and will be highly supportive of candidates who wish to either pursue academia or desire for career progression provided they show self-motivation to showcase their problem-solving abilities.

Responsibilities:
Disease modelling
Statistical analyses
Academic writing and publication of results
Preparation of meeting materials for stakeholders

Requirements:
Completed a BSc in a quantitative discipline (statistics, mathematics, computational biology, data science).
Strong programming skills (R preferred)
Statistical competence (Bayesian is advantageous)

Please email the PI at [e-mail] for further details and to arrange an interview.

More Information

Location: Kent Ridge Campus

Organization: Saw Swee Hock School of Public Health

Department : Saw Swee Hock School of Public Health