Quantitative Life Sciences is the broad application of mathematical, computational, and other quantitative methods to study biological systems at all scales—from single molecules to the environment. It is part of a rapidly expanding field that includes such specializations as systems biology, bioinformatics, biophysics, medical informatics, computational biology, computational pharmacology, computational neuroscience, and mathematical biology.
Program Requirements
Required Courses (6 credits)
QLSC 600D1 Foundations of Quantitative Life Sciences (3 credits)
QLSC 600D2 Foundations of Quantitative Life Sciences (3 credits)
QLSC 601D1 Quantitative Life Sciences Seminars 1
QLSC 601D2 Quantitative Life Sciences Seminars 1
QLSC 602D1 Quantitative Life Sciences Seminars 2
QLSC 602D2 Quantitative Life Sciences Seminars 2
QLSC 603D1 Quantitative Life Sciences Seminars 3
QLSC 603D2 Quantitative Life Sciences Seminars 3
QLSC 701 Ph.D. Comprehensive Exam
Complementary Courses
9-11 credits
Students will be required to take one or two courses from each of the Quantitative and Life Science Blocks for a total of three, stream-specific courses.
Biophysics Stream
Quantitative
BIEN 530 Imaging and Bioanalytical Instrumentation (3 credits)
BMDE 512 Finite-Element Modelling in Biomedical Engineering (3 credits)
BMDE 519 Biomedical Signals and Systems (3 credits)
CHEM 514 Biophysical Chemistry (3 credits)
CHEM 520 Methods in Chemical Biology (3 credits)
COMP 551 Applied Machine Learning (4 credits)
MATH 682 Statistical Inference (4 credits)
PHYS 519 Advanced Biophysics (3 credits)
PHYS 559 Advanced Statistical Mechanics (3 credits)
QLSC 611 Directed Readings (3 credits)
Life Sciences
BIOC 605 Protein Biology and Proteomics (3 credits)
BIOL 551 Principles of Cellular Control (3 credits)
PHGY 518 Artificial Cells (3 credits)
PHGY 520 Ion Channels (3 credits)
QLSC 611 Directed Readings (3 credits)
Computational and Statistical Molecular Biology Stream
Quantitative
BIOS 601 Epidemiology: Introduction and Statistical Models (4 credits)
BMDE 502 BME Modelling and Identification (3 credits)
COMP 551 Applied Machine Learning (4 credits)
COMP 561 Computational Biology Methods and Research (4 credits)
COMP 598 Topics in Computer Science 1 (3 credits)
HGEN 677 Statistical Concepts in Genetic and Genomic Analysis (3 credits)
MATH 523 Generalized Linear Models (4 credits)
MATH 533 Regression and Analysis of Variance (4 credits)
MATH 680 Computation Intensive Statistics (4 credits)
MATH 682 Statistical Inference (4 credits)
QLSC 611 Directed Readings (3 credits)
15 January 2023
Fecha de inicio
31 Agosto 2022, 30 Agosto 2023
McGill University
Downtown Campus,
845 Sherbrooke Street West,
MONTREAL,
Quebec (QC),
H3A 0G4, Canada
Applicants are expected to hold an undergraduate degree in one of the following areas (or equivalent): biology, chemistry, physiology, genetics, engineering, computer science, mathematics, statistics, physics, or chemistry.
Applicants must have a strong quantitative background. Such a background may be obtained by having at least the equivalent of a minor in computer science, mathematics, statistics, physics, chemistry, or engineering.
Applicants who do not have a formal education in life sciences need to have a demonstrated interest for that field, for example in the form of an undergraduate research project or the completion of life-science courses.
Applicants are expected to have attained a high scholastic standing equal to, or greater than, the minimum Cumulative Grade Point Average of 3.3 (out of 4.0 at McGill University) in all levels of study.
English Language Scores:
TOEFL (Test of English as a Foreign Language): minimum acceptable scores are: The CBT is no longer being offered. CBT results will no longer be accepted as ETS no longer reports these results. N.B. an institutional version of the TOEFL is not acceptable. IBT (Internet-Based Test): 86 overall, no less than 20 in each of the four component scores.
IELTS (International English Language Testing System): a band score of 6.5 or greater (Academic module).
Application Deadline: For Fall Term: Jan. 15.
Puede haber diferentes requisitos de IELTS en función del curso elegido.
