BMI5111 Capstone Project

BMI5111 Course Information

Integrating healthcare and data analytics is critically important for advancing biological and medical outcomes. Understanding data analytics and data science, particularly in relation to artificial intelligence, is essential to remain competitive and relevant in today’s rapidly evolving healthcare landscape. 

BMI5111 is a full-time, 13-week internship that provides students with hands-on experience in integrating bioinformatics and data analytics to address real-world problems. Through this, students will gain valuable skills in data processing, exploration, and developing insights applicable to healthcare. 

Students planning to enroll in BMI5111 in AY2025/2026 Semester 2 should approach supervisors in their field of interest.

Once the supervisor has agreed to mentor you and a project has been mutually confirmed, download and complete the project registration form, then submit it to DBMI. (Refer to the buttons on the right.)

The completed project form is to be submitted by 12 January 2026.

Learning Outcomes 

At the end of the course, students will be able to: 

  • Apply knowledge of basic and advanced clinical and biomedical concepts, clinical care processes, technologies, and workflows for the analysis, design, development, and implementation of health information systems and applications. 
  • Examine and apply concepts and methods in Biomedical Informatics to solve practical problems. 

 

Pre-Requisites  

As the capstone project requires advanced data science knowledge, students are highly recommended to only undertake capstone in their final semester. 

Project Topic 

Projects must focus on data science and/or bioinformatics, with applications in healthcare or life sciences.   

  1. Projects must focus on data science and/or bioinformatics, with applications in healthcare or life sciences. Students who are unsure whether their project fulfils these requirements may email the course coordinator, along with the completed project registration form, for clarification. 
  2. The school will not assign projects to students. Students are responsible for approaching supervisors and securing their own projects. 
  3. Students are encouraged to proactively contact the main supervisors listed in the project listing form or any other supervisor whose research aligns with their interests. A list of BMI faculty available for project queries can be found here. 
  4. The student is responsible for discussing and confirming the project with the main supervisor, and must submit the completed project registration form to Qualtrics (here) at least two weeks before the start of the semester.  
  5. The student, the supervisor, and the project must all be based in Singapore for the entire 13-week capstone period. 
  6. The main supervisor can be a staff member from a tertiary academic institution, hospital, or private industry (e.g., pharmaceutical, health data analytics, consultancy). 
  7. The main supervisor must hold either an MBBS, MD, or PhD. 
  8. The main supervisor and student should mutually agree on the project start date. Students are welcome to begin their project work before the official start date. 
  1. The main supervisor is directly responsible for supervising the project and the student registered under their supervision. The main supervisor will also serve as the primary contact for all faculty communications. Other project members or PhD students in the research group may assist as mentors, but the ultimate responsibility remains with the main supervisor.
  2. Each supervisor is advised to supervise no more than two students to ensure adequate mentorship. Exceptions may be made if additional mentoring is delegated to other project members or if the supervisor can ensure sufficient support.
  3. The main supervisor is responsible for:
    • Overseeing the progress of the student and their project. 
    • Assessing the performance of the registered student. 
    • Participating as an assessor for research projects assigned by the department, including the project report and presentation. 
    • Submitting all marks by the stipulated deadline. 
  4. Any issues concerning research projects, or conflicts between the main supervisor and the student, should be brought to the department for resolution and appropriate action. 
  1. The main supervisor and student should mutually agree on working hours, work location, and the expected weekly time commitment. Students are responsible for communicating clearly about expectations and working styles.  
  2. Students should take the initiative to provide regular updates to the supervisor. 
  3. Student must maintain confidentiality regarding any sensitive information or data encountered during the project.  
  4. Students should demonstrate respect and professionalism when interacting with colleagues. 
  5. Students should dress appropriately and professionally when working in a professional setting. 
  6. Students should address their supervisors formally, using appropriate titles such as “Dr” or “Professor” unless invited to do otherwise. 
  1. Students will be assessed on their overall work performance during the project by their main supervisor. In addition, each student will be evaluated by two examiners based on their project report and presentation. 
  2. The project report, due in Week 13 of the semester, should be approximately 5,000 words and include an abstract, introduction, methodology, results, conclusion, and references. 
  3. The project presentation will take place in Week 14. Students will deliver a 15-minute oral presentation, followed by a 10-minute Q&A session. 

Team In Charge

Prof Ngiam

NGIAM KEE YUAN

Adjunct Professor
Head, Department of Biomedical Informatics
Dr Tay - Website

TAY KAI YI

Research Fellow
Course Coordinator Biomedical Informatics
William - Website

WILLIAM LEONG

Senior Manager, Curriculum
Course Administrator Biomedical Informatics
P1000206

Our Faculty

Learn more about and connect with our diverse and distinguished DBMI faculty members for potential internships, collaborations or guidance to kickstart and align your Capstone Project.

DBMI KV (1)

Master of Science in Biomedical Informatics

Department's key programme that equips industry leaders with core skills in machine learning, data visualisation and entrepreneurship to implement clinical innovations.

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Research Opportunities

Drive healthcare in AI innovation with us: Partner with top academics and researchers at NUS Medicine to shape the future of medicine in Singapore and beyond.