Machine Learning and Regenerative Medicine Workshop
Note: This workshop is hosted online.
Application Deadline: May 9, 2023
Date: June 28 and June 30, 2023
The application process is closed.
Machine learning has the potential to revolutionize regenerative medicine research by providing new insights and enabling more efficient and effective treatments. By analyzing large amounts of data and identifying patterns that would be difficult or impossible to discern through traditional methods, machine learning can help researchers understand the underlying mechanisms of disease and identify new targets for therapy. Machine learning can be used to develop predictive models for personalized medicine or in drug screening to accelerate the process of identifying new therapeutics.
Are you interested in learning more about machine learning? Join us for our upcoming two-day workshop, “Machine Learning and Regenerative Medicine”! A panel of experts will discuss the fundamentals of machine learning, provide examples of how it can be applied in research, and describe some of the latest advancements in the field. Participants will also get hands-on experience with machine learning frameworks and tools.
Who Should Attend?
This workshop is open to any researchers (e.g., Principal Investigators, graduate students, post-docs, research associates, and/or technicians) in stem cell and regenerative medicine research in a Canadian lab who are interested in learning about machine learning. Participants in the tutorial session are encouraged to have some programming experience, particularly in Python (e.g., the ability to read and understand some code).
Workshop Learning Objectives:
- Understand some of the common applications of Machine Learning (ML) in cellular, molecular, and clinical biology;
- Be able to describe at a high level how some of the common ML algorithms work, including linear regression and neural networks, when each is applicable, and know where to look for more information;
- Understand what is meant by regression/classification, supervised/unsupervised, training/testing/tuning (validation) data;
- Be able to identify some common failure modes, considerations, and caveats on the application of ML and interpretation of ML predictions; and
- Be able to create simple ML models, evaluate them, and identify issues with their performance.
- Carl de Boer, Assistant Professor, University of British Columbia
- Kieran Campbell, Assistant Professor, University of Toronto
- Michael Hoffman, Senior Scientist/Associate Professor, University Health Network/University of Toronto
- Jennifer Mitchell, Professor, University of Toronto
- Abdul Muntakim Rafi, Ph.D. Candidate, de Boer lab, University of British Columbia
- Bo Wang, Assistant Professor, University of Toronto
Dates & Key Details
June 28, 2023, 9 a.m. – 12 p.m. PT (12 p.m. – 3 p.m. ET)
June 30, 2023, 10:30 a.m. -12 p.m. PT (1:30 p.m. – 3 p.m. ET)
This workshop will be hosted online. A link to the online sessions will be provided to successful applicants.
How to Apply
- Complete the application form here by Tuesday, May 9, 2023. As part of the application form, you will be required to email your CV to firstname.lastname@example.org.
- The SCN Training & Education Committee will review all complete applications, and applicants will be informed of the competition outcome by late April. Notification of acceptance for successful applicants will include a registration link for joining the online workshop sessions.
- Trainees should also provide a full letter of support from your current supervisor detailing how your attendance will benefit your research and the lab’s stem cell research program. Letters should be e-mailed by supervisors directly to Ellie Arnold, email@example.com, at the same time you submit your application documents. A confirmation email will be sent within 24 hours of SCN receiving the submitted support letter. If a confirmation email is NOT received from SCN within 24 hours of submission, it is the responsibility of the applicant to contact SCN and ensure that all application materials have been received by SCN.
- Applicants must be a Principal Investigator, trainee, or highly qualified personnel (HQP) (i.e., a graduate student, post-doc, research associate and/or technician currently working on a research project in the field of stem cells and regenerative medicine in a Canadian lab).
- Non-academic applicants are welcome to apply; however, academic applicants are prioritized, and seats are limited. A $500 registration fee will apply to all non-academic applicants.
- If you’re unsure whether you are a trainee/HQP, please email Ellie Arnold at firstname.lastname@example.org for confirmation.
- Applicants who demonstrate that they will apply the techniques learned in the course to their stem cell research project within one year will be prioritized.
- Note that participants in this course are required to use their personal computers, with head-set for audio and webcam for video interaction. A second monitor/screen is also highly recommended.
- Spaces are limited for this training opportunity. SCN will cover the registration costs (paid directly to the organizers) of this workshop for applicants who attend all sessions and complete all elements of the online content within the designated period. For applicants who fail to attend all sessions or complete the course content, a fee of $500 will be levied to cover the costs associated with delivering this training opportunity.
- By accepting a place in this workshop, the recipient agrees to provide a report describing the value of the training and networking opportunities made available through the award. This information will be used at SCN’s discretion on its website, newsletters and for the purpose of reporting to its funding agencies. By registering for this workshop, attendees also agree to having their pictures taken during workshop and used in materials as described above. Please note that expense reimbursement will be processed only once the completed report is received.
For further information on this workshop or application-related inquiries, please contact Ellie Arnold at email@example.com.