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Our Concentrations

Data Science
for Biology

# 10
University in Canada
# 0
Computer Science department globally
$ 25 K
average internship salary
450 +
companies represented

What is Data Science for Biology?

As a discipline, Data Science for Biology requires computational expertise with biological knowledge to advance reach and science in a rich variety of fields, such as biochemistry, medical science, molecular genetics, ecology and evolutionary biology, computer science, applied chemistry, etc. The Data Science for Biology concentration provides students with fundamental and applied research skills training to equip them to take on scientific leadership in the life sciences industry addressing biological big data challenges across Ontario, Canada, and internationally.

Graduates of the MScAC who complete the Data Science for Biology concentration will enter the multi-billion-dollar bio-economy that is experiencing tremendous growth driven by the boom of big data and potential for such exciting and transformative developments as personalized medicine, precision agriculture, consumer-focused bioproducts and services, synthetic biology etc.

Endless Career Opportunities

Discover the endless possibilities to accelerate your career as a world-class innovator.

Applied Research Scientist Big Data Engineer
Applied Research Scientist Big Data Engineer
Data Engineer Biostatistician
Data Engineer Biostatistician
Computational Biologist Machine Learning Engineer
Computational Biologist Machine Learning Engineer

Career Opportunities in Data Science for Biology

  • Applied Research Scientist

  • Bioinformatics Researcher

  • Big Data Engineer

  • Biostatistcian
  • Computational Biologist
  • Data Engineer
  • Machine Learning Engineer

Program Requirements

  • Students must successfully complete six graduate level courses (totalling 3.0 Full Course Equivalents (FCEs)) as follows:
    • 1.0 FCE chosen from the CSB/EEB/MMG/STA 1000-level or higher from the approved list (graduate courses from participating departments that have a bioinformatics or computational biology focus). This may include a maximum of 0.5 FCE chosen from EEB/MMG/STA courses. Appropriate substitutions may be possible with approval.
    • 1.0 FCE chosen from the Computer Science (CSC course designator) graduate course listings from the approved list in two different research areas as defined in the Computer Science Graduate Student Handbook, at most one of which is from Artificial Intelligence. Course selections should be made in consultation with, and be approved by, the Program Director. Appropriate substitutions may be possible with approval.
    • 1.0 FCEs required professional courses Communication for Computer Scientists (CSC 2701H) and Technical Entrepreneurship (CSC 2702H).
  • An eight-month industrial internship, CSC 2703H (3.5 FCEs). The internship is coordinated by the department and evaluated on a pass/fail basis. ‘Pass’ grades are awarded based on evaluations received from the industry/academic supervisors of the internship project and submission of an appropriately written final report, documenting the applied research internship.
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