Research Assistant (data science): Patient stratification for development of better isolation guideline
Research project: Patient stratification for development of better isolation guideline
Isolation of COVID-19 has been implemented in most countries since the pandemic started. However, the isolation guideline varies between countries. Scientifically evidenced isolation guidelines are needed. In this study, we compare different isolation guidelines, using the simulator mimicking the time course change in viral load.
This project is led by Keisuke Ejima, an Assistant Professor at Lee Kong Chian School of Medicine, Nanyang Technological University.
Key Responsibilities:
・Collect and clean data
・Analyze the data with mathematical/statistical models
・Review literature
・Involved in manuscript writing
・Additional task and research activities assigned by PI
Key Requirements and Competencies:
・Master’s degree in a quantitative field, such as data science, computational biology, mathematics, computer science, (bio)statistics, or related field.
・Research experience and/or educational background on public health and medicine is a plus but not essential.
・Computational experience on R is preferred.
・Good communication skill and respectful attitude for teamwork.
Application reviews are on-going, so apply as soon as you can. For further information about the above research opportunities, please contact Dr. Keisuke Ejima (LKCMed) keisuke.ejima [at] ntu.edu.sg.
- Type
- Other
- Institution
- Lee Kong Chiang School of Medicine, Nanyang Technological University
- City
- Novena
- Country
- Singapore
- Closing date
- May 31st, 2025
- Posted on
- March 7th, 2025 07:17
- Last updated
- March 7th, 2025 07:17
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