National University of Singapore: Research Associate (Digital Health and Data Science)

Institution (Location)
National University of Singapore
Position Description

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

Research Associate (Digital Health and Data Science), 1 year minimum, up to 3 years

A Research Associate position is available in the Saw Swee Hock School of Public Health to support the Principal Investigators in research projects in the areas of digital health and behavioural science with focus on the use of intensive longitudinal data. The position will focus on data analyses of diverse digital health data derived in observational and intervention studies using different wearable sensors and smartphone technologies.

The Research Associate will work closely with members of different research programmes:
• The Physical Activity and Nutrition Determinants in Asia (PANDA) research programme: https://blog.nus.edu.sg/sphpanda/ PANDA is one of the major research programs of the SSHSPH including faculty members from a variety of disciplines. PANDA aims to understand determinants of nutrition and physical activity behaviors in Asian populations and develop interventions to improve these behaviours and contribute to the prevention of non-communicable diseases and mental well-being.
• Continuous Observations of Behavioural Risk Factors in Asia (COBRA) study: https://blog.nus.edu.sg/sphpanda/research-projects/cutting-across-area-2-and-area-3/cobra/ COBRA is a sub-cohort of SG100k. It involves 1500 middle aged adults to understand the interactions between behavioural and environmental factors and how these relate to health. Specifically, using wearable sensors, mobile phone applications and spatial analysis, the cohort aims to identify behavioural and environmental determinants of lifestyle risk factors, which inform the design of personalised lifestyle interventions.
• Future Health Technologies (FHT) – Mobile Interventions: https://fht.ethz.ch/research/mobile-health-interventions.html FHT Module 2 applies the Multiphase Optimisation Strategy to identify and overcome individual, cultural, legal and organisational barriers and identify facilitators for the successful implementation of interventions in Singapore. The program develops smartphone-based interventions for the prevention of type-2 diabetes mellites and the promotion of mental well-being.
• In performing the data analyses, the candidate will have the opportunity to conduct methodological research in biostatistics or healthcare analytics.

Major duties and responsibilities of the position include taking the lead in extracting, managing, and analysing data from different digital health studies. In addition, the candidate is expected to lead the publication of results and findings in peer-reviewed journals.

The candidate is expected to be technically capable, hardworking and able to work independently and as a team.

Candidate’s Qualifications (who should apply)

1. Master in a quantitative discipline (e.g. data science, statistics, computer science)
2. Relevant working experience
3. Use of scripting languages and statistical software (e.g., R, STATA, Perl, Python) to manage, process and analyse (large) datasets.
4. Use of multiple data analytics tools and able to learn new tools as required.
5. Good understanding of the theory behind the data analytics tools which facilitates the conversion of raw data into useful information that addresses the research question.

How to Apply

Recruitment is open immediately, and will continue until the position is filled.

For further enquiries, please contact Dr Tan Chuen Seng at [email protected] or Dr Falk Mueller-Riemenschneider at [email protected].

Qualifications
Master in a quantitative discipline (e.g. data science, statistics, computer science)

We regret that only shortlisted candidates will be notified.

 

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