The A*STAR Institute for Human Development and Potential (A*STAR IHDP) focuses on research that aims to improve and impact the health and well-being of Singaporeans across the life course.
Job Description
Support the data management and data analytics deliverables for a cardiometabolic health study. The role focuses on data collection, monitoring, and multi-modal data integration, with a specific emphasis on Electronic Health Records (EHR), genetic/molecular epidemiologic research, and the application of Large Language Models (LLM) for data curation and analytics.
Job Responsibilities
- Apply advanced statistical and computational methods to analyze large datasets of protein or metabolite profiles.
- Implementation of effective data management processes across clinical, multi-omics, and wearables data in hybrid AWS cloud environment
- Apply Large Language Models (LLM) to extract, process, and analyze information from unstructured clinical notes and health records.
- Proactive quality control audits/quality management plans across longitudinal visits to ensure data accuracy, completeness, and proper usage of data management systems.
- Identify patterns, correlations, and predictive insights to assess patient risk stratification and disease progression.
Job Requirements
- PhD in Chemistry, Bioinformatics or Biomedical Engineering or a related field. A MSc or PhD in Data Science, Statistics, Mathematics, Computer Science, Physics or related quantitative field are also welcome to apply.
- Knowledge of genetic and molecular epidemiologic research (e.g., GWAS, polygenic risk scores, molecular data integration).
- Worked with EHR or observational human data (e.g., handling structured/unstructured data).
- Knowledge of or experience with Large Language Models (LLM) (e.g., prompt engineering, fine-tuning, or NLP for healthcare text), probabilistic modelling, transfer learning, programming in Python, R, or other languages.