Master of Science in Biomedical Data Science

Master (Coursework)

Programme Type

Full-time

Master of Science in Biomedical Data Science

msc_biodatascience@ntu.edu.sg

The Master of Science in Biomedical Data Science is the first graduate programme in the Asia-Pacific region offering data science training for specific application in the biomedical domain. The programme is a joint collaboration between Nanyang Technological University (NTU) and the Agency for Science Technology and Research (A*STAR) Singapore.  

 

The curriculum is developed by current practitioners and informed by industry experts in the pharmaceutical, healthcare and tech sectors. Unlike other taught graduate programmes, the curriculum emphasizes on hands-on learning and practical skill acquisition. You will have the opportunity to specialize in any of the 3 tracks: Bioinformatics, Biotechnology or Artificial Intelligence. 

A summary of 3 tracks offered by Biomedical Data Science
Upon graduation, you will be able to 

  1.  Demonstrate a deep understanding of applied mathematics and statistics 
  2.  Exhibit proficiency in developing and programming Data Science and AI technologies 
  3. Apply these skills meaningfully on real-world problems 

Biomedical Data Science Immersion Scheme (BMDSIS) 

What is BMDSIS? 
The biomedical data science immersion scheme (BMDSIS) is a 6 to 8-month research programme where you deepen your domain knowledge in the biosciences via internship with a professor. You also gain the opportunity to apply your skills and develop your maturity as a biomedical data scientist. Depending on the project, this may also lead towards achievements such as deployed software or publications. Such achievements are useful “stamps” that signify ability. 

Currently, you need to be enrolled in the biomedical data science masters programme to be eligible for BMDSIS. However, we will also consider masters students from relevant competitive programmes in NTU on a case-by-case basis (for example, Master of Science in Analytics or Master of Science in Artificial Intelligence). 

Can part-time students take part? 
BMDSIS students are required to spend their day times working in the labs. If you have an existing day job, this may be problematic. 

Can BMDSIS be used for graduation? 
BMDSIS is non-credit bearing. And so, it does not count towards your graduation requirements for the masters programme. 

How am I recognized for BMDSIS participation? 
You will receive a certification at the end of BMDSIS. Depending on performance, the certificate is tiered at High Distinction, Distinction or Merit. There is also an award for the best intern, with a prize and social media coverage on our NTU platforms. 

The final decision for performance tier and awards will be made jointly by the Biomedical Data Science Programme Director, the Associate Chair for Graduate Studies, and a panel comprising two other senior faculty members. 

What do I need to submit to complete my BMDSIS internship? 
Nearing the end of your internship, you need to submit a report highlighting your key achievements and findings of your internship to the graduate office (msc_biodatascience@ntu.edu.sg). There is no specified page limit, but length should be commensurate with your achievement. Do not waste words! 

To improve your competitiveness, we also ask you to submit a video recording with slides. This is optional. 

The final report submission is required to be eligible for certification. 

When does BMDSIS take place? 
Typically, trimester 1 and 2. Except for 2020 cohort, which is trimester 2 and 3. 

Can I be paid for BMDSIS? 
Usually no. However, discretionary payment can be made depending on the supervisor and the project requirements. 

Where do I sign up for BMDSIS? 
Sign-up form link: http://survey.ntu.edu.sg/efm/se/705E3EE7648F2375 
 
However, you should speak with the professors first to find out more about the project and make an informed choice. 

You also need to negotiate properly with the supervisor regarding work arrangements and expectations. 

Some professors are more selective. And would like more formal interview to ensure you are a good fit with their labs. They will indicate their preferences to the masters programme office when we confirm the allocations. 

The masters programme office will inform you of the allocation. 

Other questions 

What is expected of me? 
You need to negotiate and manage expectations between yourself and the supervisor. 
In general, you should spend at minimum 10-15 hours a week working on the project and/or interfacing with the supervisor. 

You are not expected to know all the relevant domain knowledge. The purpose of this immersion is to improve your understanding and demands of the bioscience sector, while also providing opportunity for you to develop your skills as a biomedical data scientist. 

Can I self-source BMDSIS projects externally? 
No. For purposes of accountability, calls for projects to approved professors are managed by SBS Graduate Office directly. 

What do I do if I am treated unfairly? 
You may lodge a complaint with SBS Graduate Office at msc_biodatascience@ntu.edu.sg. 

What if I want to change project? 
Strong justification (e.g. evidence of misalignment of expectations/capabilities or insufficient training/support) is required. In general, SBS Graduate Office does not entertain vexatious complaints or act as arbiters. 

In the event there is misalignment, we recommend first discussing with the supervisor to modify existing project, to provide relevant training, and/or adjust expectation. Inform SBS Graduate Office at msc_biodatascience@ntu.edu.sg so that we are aware. Keep us closely informed on developments. 

Can I take multiple BMDSIS projects? 
No. 

Can my BMDSIS project eventually become my practicum project? 

Yes. However, to ensure fairness, only the component done during the practicum phase will be evaluated. 

 

Bioinformatics, Biotechnology, Artificial Intelligence 

To find out more click here
The programme duration is one year (maximum two years) for full-time studies. Students enrolled for part-time studies may complete this over a period of two years (max four years). 

For full time students, the minimum period of candidature is 1 year, and the maximum period of candidature is 2 years. For part time students, the minimum period of candidature is 2 years, and maximum period of candidature is 4 years. 

Trimes​​ter 1​​ 

27 July 2020 – 23 Oct 2020 (13 weeks) 

Trimester 2 

9 Nov 2020 – 18 Dec 2020 (6 weeks) 

Recess week: 19 Dec 2020 – 03 Jan 2021 (2 weeks) 

04 Jan 2021 – 19 Feb 2021 (7 weeks) 

Trimester 3 

01 Mar 2021 – 28 May 2021 (13 weeks) 

12 AUs Core; 9 AUs Specialization; 9 AUs Project 

Trimester 1 
(CORE) 

Course Code 

Course Title 

AUs 

BS6200 

Essential Machine Learning for Biomedical Science 

BS6201 

Essential Programming for Biomedical Science 

BS6202 

Techniques in Biomedical Data Mining 

BS6203 

Story-telling with Graphics and Visualizations 

BS6204 

Deep Learning for Biomedical Science 

BS6205 

Essential Bio-statistics and Bio-mathematics 

Total 

12 

 

Trimester 2 
(CHOOSE ONE SPECIALIZATION) 

 

Course Code 

Course Title 

AUs 

AI Track 

BS6206 

Advanced Computational Thinking for Biomedical Data Science 

BS6207 

Advanced Artificial Intelligence for Biomedical Data Science 

BS6208 

Biological Big Data 

Bioinformatics Track 

BS6209 

Biological Sequence Analysis 

BS6210 

Biomolecular structures: modelling and design 

Select any one specialization module from AI track 

Biotechnology Track 
(Not offered in AY2020) 

(TBC) 

Drug Discovery and Development Technologies 

(TBC) 

High Throughput Technologies and Imaging 

(TBC) 

Synthetic and Systems Biology 

Total 

9 

 

Trimester 3 
(PROJECT WORK) 

Course Code 

Course Title 

AUs 

  • Research Project in BII, NTU or Industry 

  • Industry arrangements requires joint supervision 

  • Final report and Thesis Defence 

Total 

9 

Assessment and Exams 

  • Assessment for each module will be based on a final exam and/or continuous assessment which should nominally involve practical (mini project) components. 
  • The practicum will be supervised by faculty members with inputs from industrial collaborating partners (where applicable). Assessment is performed by supervisor and an examiner based on a final project report and presentation. 

 

Graduates may retool towards data-analytics or technology-oriented roles in their home companies or pursue further specialization and training in academia. These skillsets are not relevant to merely biomedical research and healthcare, and are highly sought after in other sectors such as banking and finance, energy, government, transport, etc. Experienced graduates may eventually move into strategic planning and decision-making roles using data-centric approaches.

In addition, we will also facilitate project placements in industry and government sectors. Tie-ups with data science training and placement companies e.g. UpLevel, will help you ensure that you get the best possible exposure and training opportunities.

Programme Fees

Payment Details 

Due Date 

Singaporean 

Singapore PR 

International Students 

Deposit (non-refundable) 

Upon acceptance of offer 

S$1,000 

First Payment 

Year 1, start of Trimester 1 
(for all students) 

S$16,000 

S$21,000 

S$26,500 

Second Payment 

Year 1, start of Trimester 2 
(for Full-Time students) 

S$17,000 

S$22,000 

S$27,500 

Year 2, start of Trimester 1 
(for Part-Time students) 

*All fees are inclusive of GST