Since last century, we have been witnessing a continuous booming of data in life sciences more than ever. This subdiscipline aims to equip the students with the tools and skills to overcome the challenge of extracting, analyzing, and interpreting such data in a more meaningful and systematic way. By collaboration between the Departments of Computer Science and Cell & Systems Biology, DSB uses computational tools, such as Machine Learning, statistics, infrastructure, software, and algorithms to harness life science data at all levels. From genes, molecules, cells, and tissues to the whole systems, across a wide variety of disciplines from genetics, genomics, neuroscience, physiology, ecology and evolution to biophysics – spanning across the kingdoms of microbiology, plants, and animals.
Provides students with fundamental and applied research skills training to equip them to take on scientific leadership that transforms modern life sciences industry, such as agriculture/aquaculture, brain-computer interfaces/implants, individualized medicine, pharmacology, pandemic disease control, and even climate change.
Graduates of the MScAC who complete the DSB concentration will have the choice of entering the multi-billion-dollar bio-economy, transforming life science research, but can also take leadership roles in science policy consulting.
Discover the endless possibilities to accelerate your career as a world-class innovator.
Students must successfully complete six graduate level courses (totalling 3.0 Full Course Equivalents (FCEs)) as follows:
Two courses (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.
Two courses (1.0 FCE) chosen from the Computer Science graduate course schedule two different course groups. Course groupings can be found on the Computer Science website.
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.
