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    Quantitative Life Sciences
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    Quantitative Life Sciences

    McGill University

    McGill University

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    Canada, Montreal

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    Home/Canada//McGill University/Quantitative Life Sciences
    McGill University

    McGill University

    CanadaCanada , Montreal

    Key Facts

    Program Level

    PhD (Philosophy Doctorate)

    Study Type

    Full Time

    Delivery

    On Campus

    Application Fee

    CAD 129 

    Campuses

    Main Site

    Program Language

    English

    Start & Deadlines

    Next Intake Deadlines30-Aug-2023
    Apply to this program

    Go to the official application for the university

    Duration 4 year(s)
    Tuition Fee
    CAD 10,667  / year
    Next Intake 30-Aug-2023

    Quantitative Life Sciences

    About

    Offered by: Quantitative Life Sciences     Degree: Doctor of Philosophy

    Program Requirements

    Required Courses (6 credits)

    • QLSC 600D1 Foundations of Quantitative Life Sciences (3 credits)

      Offered by: Quantitative Life Sciences (Interfaculty Studies)

      Administered by: Graduate Studies

      Overview

      QLSC : Provides an overview of important problems in the life sciences and introduces students to the latest computational, mathematical, and statistical approaches involved in their solution. Includes a survey of modern technologies for biological data acquisition and promotes a common language to communicate across the biological, physical, mathematical, and computational sciences. Topics will include bioinformatics and computational genomics, nonlinear dynamics in biological systems, linear and nonlinear models of biological signals, biophysical imaging technology, emergent behaviour in biophysical networks, and ecosystem dynamics and modeling.

      Terms: Fall 2022

      Instructors: Cook, Erik; Greenwood, Celia; Glass, Leon; Sladek, Robert; Langlais, David; Krishna, Suresh; Bashivan, Pouya (Fall)

      • Prerequisite(s): BIOL 200 or BIOL 201; COMP 206, COMP 250, MATH 314; MATH 223 or MATH 236; MATH 323 or MATH 324

      • Restriction(s): Priority given to students enrolled in the ad hoc Quantitative Life Sciences Ph.D. program.

      • No credit will be given for this course unless both QLSC 600D1 and QLSC 600D2 are successfully completed in consecutive terms.

      • Students must register for both QLSC 600D1 and QLSC 600D2

    • QLSC 600D2 Foundations of Quantitative Life Sciences (3 credits)

      Offered by: Quantitative Life Sciences (Interfaculty Studies)

      Administered by: Graduate Studies

      Overview

      QLSC : Provides an overview of important problems in the life sciences and introduces students to the latest computational, mathematical, and statistical approaches involved in their solution. Includes a survey of modern technologies for biological data acquisition and promotes a common language to communicate across the biological, physical, mathematical, and computational sciences. Topics will include bioinformatics and computational genomics, nonlinear dynamics in biological systems, linear and nonlinear models of biological signals, biophysical imaging technology, emergent behaviour in biophysical networks, and ecosystem dynamics and modeling.

      Terms: Winter 2023

      Instructors: Cook, Erik; Nadon, Robert; Grant, Audrey; Diatchenko, Luda; Oyama, Tomoko; Poline, Jean-Baptiste (Winter)

      • Prerequisite(s): BIOL 200 or BIOL 201; COMP 206, COMP 250, MATH 314; MATH 223 or MATH 236; MATH 323 or MATH 324

      • Restriction(s): Priority given to students enrolled in the ad hoc Quantitative Life Sciences Ph.D. program.

      • Prerequisite: QLSC 600D1

      • No credit will be given for this course unless both QLSC 600D1 and QLSC 600D2 are successfully completed in consecutive terms.

    • QLSC 601D1 Quantitative Life Sciences Seminars 1

      Offered by: Quantitative Life Sciences (Interfaculty Studies)

      Administered by: Graduate Studies

      Overview

      QLSC : QLS Monthly Seminar Series and Journal Club.

      Terms: Fall 2022

      Instructors: There are no professors associated with this course for the 2022-2023 academic year.

      • Students must register for both QLSC 601D1 and QLSC 601D2

      • No credit will be given for this course unless both QLSC 601D1 and QLSC 601D2 are successfully completed in consecutive terms

      • Restriction: Restricted to students enrolled in QLS.

    • QLSC 601D2 Quantitative Life Sciences Seminars 1

      Offered by: Quantitative Life Sciences (Interfaculty Studies)

      Administered by: Graduate Studies

      Overview

      QLSC : See QLSC 601D1 for description.

      Terms: Winter 2023

      Instructors: There are no professors associated with this course for the 2022-2023 academic year.

      • Prerequisite: QLSC 601D1

      • No credit will be given for this course unless both QLSC 601D1 and QLSC 601D2 are successfully completed in consecutive terms.

      • Restriction: Restricted to students enrolled in QLS.

    • QLSC 602D1 Quantitative Life Sciences Seminars 2

      Offered by: Quantitative Life Sciences (Interfaculty Studies)

      Administered by: Graduate Studies

      Overview

      QLSC : QLS Monthly Seminar Series and Journal Club.

      Terms: Fall 2022

      Instructors: There are no professors associated with this course for the 2022-2023 academic year.

      • Students must register for both QLSC 602D1 and QLSC 602D2

      • No credit will be given for this course unless both QLSC 602D1 and QLSC 602D2 are successfully completed in consecutive terms

      • Restriction: Restricted to students enrolled in QLS.

    • QLSC 602D2 Quantitative Life Sciences Seminars 2

      Offered by: Quantitative Life Sciences (Interfaculty Studies)

      Administered by: Graduate Studies

      Overview

      QLSC : See QLSC 602D1 for description.

      Terms: Winter 2023

      Instructors: There are no professors associated with this course for the 2022-2023 academic year.

      • Prerequisite: QLSC 602D1

      • No credit will be given for this course unless both QLSC 602D1 and QLSC 602D2 are successfully completed in consecutive terms

      • Restriction: Restricted to students enrolled in QLS.

    • QLSC 603D1 Quantitative Life Sciences Seminars 3

      Offered by: Quantitative Life Sciences (Interfaculty Studies)

      Administered by: Graduate Studies

      Overview

      QLSC : QLS Monthly Seminar Series and Journal Club.

      Terms: Fall 2022

      Instructors: There are no professors associated with this course for the 2022-2023 academic year.

      • Students must register for both QLSC 603D1 and QLSC 603D2

      • No credit will be given for this course unless both QLSC 603D1 and QLSC 603D2 are successfully completed in consecutive terms.

      • Restriction: Restricted to students enrolled in QLS.

    • QLSC 603D2 Quantitative Life Sciences Seminars 3

      Offered by: Quantitative Life Sciences (Interfaculty Studies)

      Administered by: Graduate Studies

      Overview

      QLSC : See QLSC 603D1 for description.

      Terms: Winter 2023

      Instructors: There are no professors associated with this course for the 2022-2023 academic year.

      • Prerequisite: QLSC 603D1

      • No credit will be given for this course unless both QLSC 603D1 and QLSC 603D2 are successfully completed in consecutive terms

      • Restriction: Restricted to students enrolled in QLS.

    • QLSC 701 Ph.D. Comprehensive Exam

      Offered by: Quantitative Life Sciences (Interfaculty Studies)

      Administered by: Graduate Studies

      Overview

      QLSC : Compulsory comprehensive examination to evaluate the students' ability to carry out, present, discuss and defend research in their field of interest. The examination must be completed within the first 18 months of enrollment in the program.

      Terms: Fall 2022, Winter 2023

      Instructors: Greenwood, Celia (Fall) Greenwood, Celia (Winter)

    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)

      Offered by: Bioengineering (Faculty of Engineering)

      Overview

      BIEN : Microscopy techniques with application to biology and medicine. Practical introduction to optics and microscopy from the standpoint of biomedical research. Discussion of recent literature; hands-on experience. Topics include: optics, contrast techniques, advanced microscopy, and image analysis.

      Terms: Winter 2023

      Instructors: Hendricks, Adam (Winter)

      • Prerequisite: Permission of instructor.

      • (3-1-5)

    • BMDE 512 Finite-Element Modelling in Biomedical Engineering (3 credits)

      Offered by: Biomedical Engineering (Faculty of Engineering)

      Overview

      Biomedical Engineering : General principles of quantitative modelling; types of models; principles of the finite-element method, primarily as applied to mechanical systems; introduction to the use of finite-element software; model generation from imaging data; modelling various material types, mainly biological; model validation.

      Terms: Fall 2022

      Instructors: Funnell, Robert (Fall)

      • (3-0-6)

      • Prerequisite: Differential equations (MATH 271 or equivalent) or permission of instructor

    • BMDE 519 Biomedical Signals and Systems (3 credits)

      Offered by: Biomedical Engineering (Faculty of Engineering)

      Overview

      Biomedical Engineering : An introduction to the theoretical framework, experimental techniques and analysis procedures available for the quantitative analysis of physiological systems and signals. Lectures plus laboratory work using the Biomedical Engineering computer system. Topics include: amplitude and frequency structure of signals, filtering, sampling, correlation functions, time and frequency-domain descriptions of systems.

      Terms: Fall 2022

      Instructors: Kearney, Robert E (Fall)

      • (3-0-6)

      • Prerequisites: Satisfactory standing in U3 Honours Physiology; or U3 Major in Physics-Physiology; or U3 Major Physiology-Mathematics; or permission of instructor

    • CHEM 514 Biophysical Chemistry (3 credits)

      Offered by: Chemistry (Faculty of Science)

      Overview

      Chemistry : Physical chemistry concepts needed to understand the function of biological systems at the molecular level, including the structure, stability, transport, and interactions of biological macromolecules.

      Terms: This course is not scheduled for the 2022-2023 academic year.

      Instructors: There are no professors associated with this course for the 2022-2023 academic year.

      • Winter

      • Prerequisite: CHEM 203 or CHEM 204 or CHEM 223 and CHEM 243, or permission of instructor.

      • Restriction: Not open to students who have taken CHEM 404.

    • CHEM 520 Methods in Chemical Biology (3 credits)

      Offered by: Chemistry (Faculty of Science)

      Overview

      Chemistry : An overview of advanced techniques at the leading edge of Chemical Biology, including some or all of: biological imaging, kinetics of enzyme inhibition, combinatorial synthesis, atomic force microscopy of biological molecules, self assembling biomimetic structures, oligonucleotide therapeutics, biomolecular X-ray crystallography, computational methods, and nuclear magnetic resonance applied to protein interactions.

      Terms: Fall 2022

      Instructors: Kostikov, Alexey; Mauzeroll, Janine; Mittermaier, Anthony; Thibodeaux, Christopher (Fall)

      • Fall

      • Prerequisites: BIOL 200 and CHEM 345 and CHEM 302, or permission of instructor

    • COMP 551 Applied Machine Learning (4 credits)

      Offered by: Computer Science (Faculty of Science)

      Overview

      Computer Science (Sci) : Selected topics in machine learning and data mining, including clustering, neural networks, support vector machines, decision trees. Methods include feature selection and dimensionality reduction, error estimation and empirical validation, algorithm design and parallelization, and handling of large data sets. Emphasis on good methods and practices for deployment of real systems.

      Terms: Fall 2022, Winter 2023

      Instructors: Li, Yue (Fall) Rabbany, Reihaneh (Winter)

      • Prerequisite(s): MATH 323 or ECSE 205 or ECSE 305 or equivalent

      • Restriction(s): Not open to students who have taken or are taking COMP 451. Not open to students who have taken or are taking ECSE 551.

      • Some background in Artificial Intelligence is recommended, e.g. COMP-424 or ECSE-526, but not required.

    • MATH 682 Statistical Inference (4 credits)

      Offered by: Mathematics and Statistics (Faculty of Science)

      Administered by: Graduate Studies

      Overview

      Mathematics & Statistics (Sci) : Conditional probability and Bayes’ Theorem, discrete and continuous univariate and multivariate distributions, conditional distributions, moments, independence of random variables. Modes of convergence, weak law of large numbers, central limit theorem. Point and interval estimation. Likelihood inference. Bayesian estimation and inference. Hypothesis testing.

      Terms: Fall 2022

      Instructors: Alam, Shomoita (Fall)

      • Prerequisite: MATH 141 or equivalent

      • Restrictions: Not open to students who have taken MATH 324, MATH 357, MATH 557. Intended for graduate students working on quantitative research questions related to life sciences who have had differential and integral calculus.

    • PHYS 519 Advanced Biophysics (3 credits)

      Offered by: Physics (Faculty of Science)

      Overview

      Physics : An advanced biophysics course, with a special emphasis on stochastic and out of equilibrium physical processes in living matter.

      Terms: Winter 2023

      Instructors: Bourassa, François (Winter)

      • Prerequisites: (PHYS 329 or PHYS 333 or PHYS 362 or MATH 437) and (PHYS 340 or PHYS 350), or permission of the instructor.

    • PHYS 559 Advanced Statistical Mechanics (3 credits)

      Offered by: Physics (Faculty of Science)

      Overview

      Physics : Scattering and structure factors. Review of thermodynamics and statistical mechanics; correlation functions (static); mean field theory; critical phenomena; broken symmetry; fluctuations, roughening.

      Terms: Fall 2022

      Instructors: Coish, Bill (Fall)

      • Fall

      • 3 hours lectures

      • Restriction: U3 Honours students, graduate students, or permission of the instructor

    Disciplines

    Interfaculty Studies

    Requirements

    Entry Requirements

    All applicants, regardless of country of origin or educational backgrounds must meet these minimum academic requirements:

    • A Bachelor's degree (or equivalent as recognized by McGill University) in a subject closely related to the one selected for graduate work.
      • Unless otherwise noted, the Master’s program at McGill requires the completion of a four-year degree in a related area at a recognized institution. Admission to a doctoral degree requires the completion of a Master’s degree in a related area at a recognized institution.
      • The minimum Cumulative Grade Point Average (CGPA) is 3.0 out of a possible 4.0, or a Grade Point Average (GPA) of 3.2 out of 4.0 in the last two years of full-time studies. In some departments, however, a higher CGPA is required for admission. Consult your program requirements for details.
      • Your educational credentials will be assessed for equivalency with a McGill University degree. Please consult the Degree Equivalency page for more information.
    • Proficiency in English: The primary language of instruction at McGill is English. You may make arrangements to write papers, examinations or theses in French, except in cases where knowledge of the English language is one of the objectives of the course. Prior to admission, you may need to demonstrate an adequate level of proficiency in English. For more information, visit the English Language Proficiency page.

    Fee Information

    Tuition Fee

    CAD 10,667 

    Application Fee

    CAD 129 

    How to Apply

    1. Apply online

      • For a non-refundable fee of $129.03, you can submit up to two applications in the same term to two different programs. Certain programs require additional fees.

      • Do not select both the Thesis option and the Non-Thesis option for the same program as you can make this change after submitting your application.

        If applying to Mechanical Engineering or Masters of Engineering, you must apply to both the Thesis option and the Non-Thesis option if you want to be considered for both.

      • You can stop and save your progress at any time. The application will only be processed once you have submitted.
      • Once you have submitted your application an acknowledgement will be sent to the email address you have included in your application. You will be able to track your application via the online application system
      • Submit your supporting documents online. You must upload copies of your transcripts from each university-level institution you have attended, as well as other documents stipulated by the department you have applied to. A list of the required documents will be accessible on the online application system. Additional supporting documents submitted by mail or email will not be included in your application.

    2. Submit your supporting documents

      Applicants are required to provide supporting documents with their application. You should upload all supporting documents except for official transcripts, test scores and letters of recommendation. McGill will request letters of reference on your behalf from referees you identify on the application form.

      For any additional application instructions or details about the documents being requested (i.e. Statement of Purpose, Writing Sample, Academic C.V.), please refer to the program page for the academic unit you are applying to. If you have any additional questions or concerns, please do not hesitate to contact the department you have applied to.

    3. Submit your test scores

      Where applicable, arrange for test scores (TOEFL, GMAT, GRE) to be sent to McGill directly from the testing agency. You must indicate the McGill University institution code: 0935

    McGill University

    Quantitative Life Sciences

    McGill University

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    Canada,

    Montreal

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