In collaboration with the Institute for Management & Innovation, MBiotech offers its students—and students across the IMI portfolio of professional graduate programs—a rich vein of electives from which to choose when completing their degree requirements. Whatever courses you select to take, all of our electives are designed to offer advanced learning opportunities at the interface of traditional disciplines, such as Business, Data Science and the Life Sciences, and serve as capstone experiences for our graduates as they launch their careers.
› How to Enrol in an Elective
Graduate students who wish to enroll in any of the courses on this page must—
| 1 › | Complete a Course Add/Drop Form, |
| 2 › | Have the completed form authorised by the Graduate Coordinator of your home department, and |
| 3 › | Submit the signed form via email to Ortensia Qendro, MBiotech, ortensia.qendro@utoronto.ca. |
Students CANNOT enrol themselves directly on Acorn/ROSI.
› Elective Course Descriptions
All of the electives offered by MBiotech are described in this section, except for the Work Term III { BioPh · DHT } elective.
BTC1896H › Technology & Cognitive Performance
Session: Fall
Instructors: Jayson Parker
Credits: 0·5 E
Open To: U of T Graduate Students, with priority given to the following programs—
› MBiotech BioPh Stream
› MBiotech DHT Stream
› Psychology
Course Description
This new elective course looks at modern developments in neuroscience and cognitive psychology, that point to new uses of technology to enhance brain function. The course builds its foundation with a neuroanatomy primer, as well as an introduction to the cognitive neuroscience of daydreaming. How can technology be used to aid attention to avoid critical errors? How can better sleep and acts of creativity be supported by emerging technologies? In what way can video games be an aid and a burden to brain function? The major project for the course will explore digital biomarkers for cognitive performance.
Session | Topic |
I | Basic Neuroanatomy Primer |
II | Neuroscience of Day Dreaming |
III | Neuroscience of Attention: Technology Applications Part 1 |
IV | Neuroscience of Attention: Technology Applications Part 2 |
| NO CLASS | |
V | Neuroscience of Creativity: How can we enhance it with current technology |
VI | Video Games: Applications to Enhance Cognitive Function & Neuroanatomy |
VII | Large Language Models (Chat GPT) as an Aid to Cognition: Limitations and Current Unknowns |
VIII | Student Individual Project Talks Part I |
IX | Student Individual Project Talks Part II |
X | Student Individual Project Talks Part III |
XI | Course Wrap-Up and Review |
XII | Final Exam |
BTC2100Y › Thesis in Biotechnology
Session: Fall & Winter
Instructors: Scott Prosser or Jayson Parker
Credits: 1·0
Open To: Students in the Master of Biotechnology
Course Description
The Thesis research project is conducted by a faculty member the student has identified and confirmed a project for this course. The research must be original and stand as a potential contribution to the field of study for the topic in question. The topic should relate to some aspect of biopharma or digital health. A thesis study is conducted over two semesters and culminates in a written paper and a short presentation to the instructor and at least one other faculty member. The thesis involves more work than a supervised study. This reflects additional training time for the student and time for the student to conduct the research in question.
Process
If you are interested in doing this research course as an elective, follow these steps:
- Speak with a faculty member who is willing to supervise you and both have negotiated the terms around time commitment and scheduling
- Once confirmed, e-mail us at MBiotech@utoronto.ca with your supervisor, project name and the course code and ensure you CC your supervisor and we will enroll you
NOTE: For the DHT Stream, Jayson Parker will predominately be the supervisor for DHT projects. For the BioPharma Stream, Stephen Mac will predominately be the supervisor for BioPharma projects. Should your research interests align with a different faculty member, you are still able to work with another supervisor from our Faculty if they agree to supervise you.
BTC2110H › Supervised Study
Session: Fall or Winter
Instructor: TBD
Credits: 0·5 E
Open To: MBiotech Students
Course Description
The supervised research project is conducted by a faculty member the student has identified and confirmed a project for this course. The research must be original and stand as a potential contribution to the field of study for the topic in question. The topic should relate to some aspect of biopharma or digital health. A supervised study is conducted over a single semester and culminates in a written paper and a short presentation to the instructor and at least one other faculty member
Process
If you are interested in doing this research course as an elective, follow these steps:
- Speak with a Faculty member who is willing to supervise you and both have negotiated the terms around time commitment and scheduling
- Once confirmed, e-mail us at MBiotech@utoronto.ca with your supervisor, project name and the course code and ensure you CC your supervisor and we will enroll you
NOTE: For the DHT Stream, Jayson Parker will predominately be the supervisor for DHT projects. For the BioPharma Stream, Stephen Mac will predominately be the supervisor for BioPharma projects. Should your research interests align with a different faculty member, you are still able to work with another supervisor from our Faculty if they agree to supervise you.
BTC2120H › Decision Analytics in Business, Healthcare & Management
Session: Winter
Instructor: Ningyuan Chen
Credits: 0·5 E
Open To: UofT Graduate Students, with priority given to the following programs—
› MBiotech BioPh Stream
› MBiotech DHT Stream
› Master of Management & Innovation (MMI)
Course Description:
Data analysis and decision making are two core components in many industries. In this course, we will walk through major techniques in both components, including descriptive and exploratory data analysis, predictive analytics, causal inference, optimization and simulation. The students are expected to conformably answer the following questions upon the completion of the course: how to visualize and present data to your clients or managers, how to predict patterns in the future from the historical data, how to measure the effectiveness of a policy, how to make best decisions under uncertainty based on the available information.
› IMI Electives
Students can also select from a number of electives offered by the Institute for Management and Innovation that allow them to focus on their individual areas of interest (science or management concentration). These selections need to be approved in advance by the MBiotech Program Director and the Chair/Director of the host department. Please note that availability of electives offered in MBiotech and other host graduate departments is subject to change each year, and dependent upon semester. Like all graduate programs at UofT, each department enrols their own program students in their electives first and, if there is space available, accepts other program students from other graduate programs, in their elective courses.
› MBiotech students are also eligible to take any graduate-level elective course offered at the University of Toronto, with Directors’ approval. Elective course specifics would be available from the host department and some elective courses require specific course prerequisites.