Job Description

Position: Research Assistant

Appointment Period: 1 year (initial contract), extendable to 2–3 years based on performance

Duties and Responsibilities

The appointee will support the project leader in the following areas:

Big Data Analytics & Computational Research

• • Process, clean, and analyze large-scale clinical datasets (e.g., EHRs, sensor data) using advanced tools (e.g., Python/R, SQL, Hadoop/Spark).
  • Develop predictive models (e.g., machine learning, NLP) to identify delirium risk factors and optimize prevention strategies.
  • Maintain and optimize databases for high-volume data storage, integration, and retrieval.
  • Collaborate with data engineers to design pipelines for real-time data streaming and analysis.

Qualifications

• • Bachelor’s/Master’s degree in Data Science, Nursing, Public Health, Psychology, or Computational Social Sciences.
  • Proven experience in big data analytics:
    • Proficiency in programming (Python/R, SQL) and big data tools (e.g., Spark, TensorFlow/PyTorch).
    • Hands-on experience with machine learning frameworks (e.g., scikit-learn, Keras) and cloud platforms (AWS/Google Cloud).
  • Familiarity with statistical software (SPSS, STATA, SAS) and data visualization tools (Tableau, Power BI).
  • Strong understanding of clinical research workflows (e.g., REDCap, EHR integration).
  • Excellent communication skills to liaise with clinicians, data engineers, and patients.
  • Fluency in English; proficiency in additional languages (e.g., Mandarin, Malay) is a plus to communicate with research participants who speak other languages

Application

Remuneration & Benefits

• Competitive salary aligned with qualifications.
• Opportunities for co-authorship, conference attendance, and professional development.

Application Process: Submit your CV, cover letter, and expected salary to Dr Zeng Yingchun (Email: zengy25@nus.edu.sg).

More Information

Location: Kent Ridge Campus

Organization: Yong Loo Lin School of Medicine

Department : Alice Lee Centre for Nursing Studies

Employee Referral Eligible: No

Job requisition ID : 28744