Program Description
MUlti-Scale multi-modal Image and omics Computing for health (MUSIC)” is a new interdisciplinary NSERC CREATE program that intends to respond to an acute need for a multi-faceted, data-driven approach to understanding the biological processes that lead to disease. Our goal with the program is to teach a multidisciplinary cohort of trainees from engineering, computer science, and medicine. MUSIC is a unique program in Canada that provides comprehensive training that integrates AI/machine learning skills with imaging and omics biological data across multiple scales and modalities.
Joining the Program
To make this program successful, we are prioritizing trainees (MASc and PhD students) who are undertaking interdisciplinary projects with multidisciplinary co-supervisors or collaborators. Please note that any interested Graduate students must be nominated for the program by their supervisors. Please reach out to your supervisor about nomination for the program.
Trainees will have a broad training experience including (a) getting familiar with various biomedical data types (at various scales) and how AI/machine learning could be utilized to analyze biomedical data, (b) industry or academic internships, and (c) professional development opportunities (including mentorship programs). Through the MUSIC program, we intend to create two graduate-level courses, outlined below. Note, the first cohort of the program (Jan 2024) will not be required (but encouraged) to take these courses. However, professional development and cohort activities as well as internships will be required to be fulfilled.
Nominations due by March 31
Program Details
MUSIC Program Graduate Student Awards
If a graduate student is selected as an awardee, their supervisor will receive $18,000 (MASc) or $27,000 (PhD) spread across two (MSc) or three (PhD) years. Note, this amount is a research grant to the supervisor to cover the cost of current RAships. Therefore, decision to top-up a student’s RAship is at the sole discretion of the supervisor. If the graduate student holds a major award/fellowship (e.g., NSERC CGS M/D), MUSIC will top up to $30,000 (MASc) or $45,000 (PhD) for 1 year.
Graduate Student Program Requirements
1) Course 1: Biomedical Data Fundamentals (3 credits, course description below, hosted by SBME)*
2) Course 2: Machine Learning (ML) in Medicine (3 credits, course description below, hosted by SBME)*
*Note, the first cohort of the program (Jan 2024 intake) will not be required (but encouraged) to take these courses that will be offered in Sep 2024. Other course requirements are dictated by the home department where the trainee is doing their graduate studies.
In addition to the above, the trainees are required to participate in the following activities spread across their graduate program (total of 36 hours over the first two or three years of MSc or PhD programs):
3) Mentors program (minimum of 2 hours total of training)
4) Professional Craftsmanship (minimum of 12 hours total of training)
5) Training in EDI (minimum of 2 hours total of training)
6) Annual Showcase (1 per year; full day)
7) Ethics & Regulatory Workshops of AI in Medicine (minimum of 5 hours total of training)
8) Monthly Emerging Topics Lectures (minimum of 12 hours total of training)
9) Industry or academic internship (min. one per degree; 3-4 months)
Course 1) Biomedical Data Fundamentals: In this course, an overview of molecular, cellular and clinical imaging, and omics technologies and their relationship with each other will be covered. This new course will cover various biological or medical imaging and omics modalities, including the advantages and limitations of each technology, and provide awareness and understanding of how they are brought together in modern biomedical studies to capture data from micro to macro scales. The course will have three modules: Module 1: Modern Biomedical Multi-Modal Multi-Scale Studies, Module 2: Molecular & Cellular Imaging and Omics, Module 3: Clinical Imaging. As part of this course, we will introduce weekly student-driven “Discovery” sessions, where students come together for a deep dive into all facets of multi-modal multi-scale data in relation to a specific pathology, facilitated by one or more post-graduates and faculty. These sessions will provide opportunities for trainees to acquire collaboration, communication, and interdisciplinary problem-solving skills on top of technical competencies.
Course 2) Machine Learning (ML) in Medicine: A lecture and project-based course focused on applying ML techniques to solve real biomedical problems. Weekly “Discovery” sessions will continue in this course by bringing ML to multi-modal multi-scale data. In this course, the students will acquire hands-on experience with various data modalities and how ML can be applied to these data types.
Frequently Asked Questions
1. Is the MUSIC CREATE program open to international students?
Yes. The MUSIC CREATE program is open to both domestic and international graduate students at UBC.
2. Does the program provide student funding?
Yes. Each student accepted into the program receives $27,000 in total funding over three years (i.e., $9,000 per year).This funding is awarded to the supervisor, who determines how it is allocated to the student.
3. Is the $27,000 provided per year or over three years?
The total funding is $27,000 total over three years, not per year. For accounting and reporting purposes, we may disburse funds towards the end of Year 1.
4. Are there extra courses I need to take as part of the MUSIC CREATE program?
Yes. Students are required to complete additional interdisciplinary coursework to enrich their training in imaging, omics, and computing.
You can find the full list of required and elective courses on the Program Curriculum section of this page.
6. Does my supervisor need to be affiliated with SBME?
No. Your primary supervisor must be a UBC faculty member, but they do not need to be from the School of Biomedical Engineering (SBME). Supervisors from other departments are welcome.
7. Can my co-mentor or collaborator be outside UBC or SBME?
Yes. Collaborators and co-mentors can be outside SBME and may also be external to UBC, depending on the research project. Interdisciplinary and cross-institutional collaborations are encouraged.
8. How do I apply or get nominated for the MUSIC CREATE program?
Students are nominated by their supervisor. Supervisors must submit a nomination package that includes the student’s academic background, proposed research, and alignment with the program’s goals. Details on nomination procedures and deadlines are provided on the Application Process section of this page.
9. Can students already enrolled in a UBC graduate program join MUSIC CREATE?
Yes. The program is open to current graduate students at UBC who meet the eligibility criteria and are nominated by their supervisor. However, priority will be given to incoming students or students who have started recently so that they have enough time to complete the requirements of the program.
10. What are some background requirements in order to be nominated for the MUSIC CREATE program?
Ideal candidates are those who have demonstrated academic and/or research excellence in their field and show strong potential to contribute to interdisciplinary projects combining imaging, omics technologies, and computing. We are prioritizing trainees (MASc and PhD students) who have a passion for cross-disciplinary collaboration and innovation in biomedical and translational health research. Prior coursework in software engineering and machine learning is preferred. Students without such background will require to take two pre-requisite courses.
11. Is there a deadline for nominations?
Yes. Nomination deadlines are announced on this website and via program communications. Please check the Application Process section.
Contact Us
If you have questions about this program or would like to learn more, please contact Dr. Ali Bashashati.