Overview

The Master of Science in Biostatistics and Biomedical Data Science (MSc BBDS) combines rigorous training in biostatistics, data science and AI with a strong focus on biomedical research and healthcare.  It equips students with the methodological and analytical skills to address complex challenges across the clinical and biomedical data spectrum.

The programme offers two tracks—Biostatistics and AI, and Bioinformatics and AI—providing specialised training in diverse domains of biomedical science. Courses are taught by leading faculty and data science practitioners from Duke-NUS Medical School and the National University of Singapore (NUS), combining methodological expertise with real-world biomedical applications.

Learning Outcomes

Apply Advanced Data Science Methods
Apply statistical, machine learning, and computational biology methods to analyse clinical and biomedical data for actionable insights.

Integrate Interdisciplinary Knowledge
Integrate knowledge from medicine, biology, and quantitative methods to address complex problems in translational biomedical and clinical research.

Communicate Effectively and Responsibly
Communicate analytical findings clearly to diverse stakeholders while applying ethical principles to the use of biomedical data and AI.

Who should apply

Our program welcomes local and international applicants with strong quantitative skills and an interest in biomedical and healthcare applications.

Programme Structure

Two specialised tracks:

📊 Biostatistics and AI
Focuses on biostatistical methods, machine learning, and AI applied to clinical, patient-level, and population-level data to improve patient care, optimize clinical trials, and strengthen health interventions.

🧬 Bioinformatics and AI
Focuses on computational biology and AI-driven methods to analyse high-throughput genomics and omics data, support drug discovery, and advance precision and personalized medicine.

Work with a faculty supervisor to apply advanced statistical and computational methods to address a real-world biomedical or healthcare research problem.

Application Now Open!

Aug 2027
Intake

1 Oct 2026 - 30 Apr 2027
Application period

- Apply early to secure your place! 
 - Batch releases from February through May 2027

Application Steps

Step 1: Submit Your Online Application
Complete and submit the online application for the MSc in Biostatistics and Biomedical Data Science (BBDS) programme through the official application portal. 

APPLY NOW 

Step 2: Pay the Application Fee
After submitting your application, applicants are required to pay a non-refundable application fee of SGD 50.00, plus applicable GST, using the payment methods available on the application portal and following the instructions provided.

Application Fees

 
Step 3: Save Your Payment Receipt and Application ID
After making the payment, please keep a copy of your payment receipt and note your application ID for reference.

Step 4: Email Your Payment Details Within Two Weeks
Within two weeks of submitting your programme application, please email the following information to msc.bbds@duke-nus.edu.sg:
• Your full name
• Your application ID
• A copy of your application fee payment receipt

Please use the following email subject line: MSc BBDS Application Fee Payment – [Your Full Name] – [Application ID]

* Important: Please ensure that your payment receipt and application ID are emailed to the designated email address within the two-week deadline so that your payment can be identified and verified.

Thank you for your interest in the MSc BBDS programme. We look forward to receiving your application!

Tution Fee & Structure

"At MSc BBDS, we train the next generation of biomedical data scientists to drive the future of biomedical discovery. Our curriculum combines methodological depth with the versatility to address a wide range of challenges across the biomedical data landscape, grounded in biostatistics, trustworthy AI, and computational biology. Through our collaboration with Duke University, NUS, and Singapore Health Services (SingHealth), students gain hands-on exposure to real-world clinical and biomedical data through coursework and their master’s thesis."

 A/Prof Fan Qiao & A/Prof Bibhas Chakraborty,
Programme Directors

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