6 October 2022

Overview

This document

http://www.math.mcmaster.ca/bolker/misc/gradinfo_2022.html

Why go to graduate school?

  • Because you like/are good at learning stuff
  • Enhanced job opportunities
    • Academia
    • Industry
    • Government

What do graduates do after finishing?

  • More school (M.Sc. → Ph.D.)
  • Fields that used advanced analytical/quantitative skills:
    • financial math
    • statistics
    • data science/analytics (insurance, banks, …)
    • scientific computing
  • Professional school (law, business, teachers’ college, etc.)
  • Ph.D. graduates often go to academia, but also skilled positions in industry/government

(My students: academics, banks, location analytics, applied biology [fisheries/conservation], public health)

Where?

  • big versus small universities
  • critical mass in your field of research interest
  • supervisor
  • $$, requirements, etc.
  • which country?
    • almost anywhere: Canada, US, UK, Europe, Australia, Brazil …
    • look for scholarships etc.
    • maybe opportunity to travel during your degree

Grad school at Mac

Research and training opportunities in

  • pure and applied mathematics (“mathematics”)
  • statistics and big data (“statistics”)
  • scientific computing and computational science (“CSE”)
  • financial math (“M-Phimac”)

What to expect in Grad School?

  • Courses, TA responsibilities, seminars, …
  • Research may start right away or within a year - finding a supervisor is essential!
  • At Mac: may transfer directly from M.Sc. to Ph.D. 
  • Direct entry to Ph.D. programs common in the US
  • Qualifying and/or comprehensive exams in most Ph.D. programs

Mathematics degrees

Research areas

See web page

  • algebra, algebraic geometry, number theory
  • analysis
  • applied math (mostly ODEs and PDEs)
  • geometry and topology
  • math biology
  • mathematical logic/model theory

Project and thesis M.Sc. in Mathematics

  • project-based M.Sc. in less than 12 months!
  • gain knowledge and experience prior to professional program or Ph.D.
  • possible joint-degree “cotutelle” programs

Statistics degrees

Coursework master’s

  • Core courses: STATS 743 (A&B), 770 (A&B), 771 (A&B), 752
  • Four additional courses are required:
    • Four 700-level STATS courses; or
    • Three 700-level STATS courses plus one 600-level STATS course; or
    • Two 700-level STATS courses plus two 600-level STATS courses.
  • Substitutions possible
  • Typically completed in two or three terms.

Thesis master’s

  • Core courses: STATS 743 (A&B), 770 (A&B), 752
  • Thesis plus 3 additional courses
    • Three 700-level STATS courses; or
    • Two 700-level STATS courses plus one 600-level STATS course; or
    • One 700-level STATS course plus two 600-level STATS courses.
  • Thesis \(\approx\) two one-term 700-level courses
  • Typically defend thesis in term 3 or 4
  • Discuss the thesis expectations and timeline with your supervisor.
  • Must have a willing supervisor to be accepted, but not necessary at the time of application

PhD

  • No core courses: course requirement varies
    • With an M.Sc. degree in Statistics/related area, or transfer into Ph.D. from M.Sc.: two 700-level STATS (or comparable) courses.
    • With a B.Sc. Statistics/related area: 4 700-level STATS (or comparable) courses.
  • Coursework must be approved by the supervisor.
  • M.Sc. → Ph.D. transfer is common
  • Comprehensive part 1 (written, January of first year); part 2 (written report + oral exam, term 3 or 4)
  • Thesis: defend after 4 years

CSE degrees

Computational Science and Engineering

  • interdisciplinary “school” at McMaster
  • crosses Science, Engineering, de Groote School of Business (Health Sciences)
  • 60+ supervisors across these programs (lots in math & stats)

areas

  • scientific computing, typically numerical
  • fluid mechanics, optimization, epidemic models, data science …
  • not software engineering
  • not computer science

grad programs

  • project master’s (16 months)
  • thesis master’s (24 months)
  • PhD (4 years)

coursework

  • CSE 700, 701; C++ programming and numerical analysis
  • CSE 780/790 (data science, statistical learning)
  • CSE 745/746 (parallel computation)
    • many cross-listed courses: optimization, neuroscience, …
  • bi-weekly seminar

what are we looking for?

  • math (at least linear algebra; preferably numerical analysis, diff eqs, real analysis …)
  • some computation: R, Python, C++ …

Application procedures

Applying (Mac and in general)

  • Most programs require a B+ honours degree (average based on math courses taken in last one or two years)
  • Admission to some programs can be very competitive; minimum grade averages are not indicative …
  • Lots of information available online:
    • websites, social media, Graduate Ambassadors
    • Email grad advisors and potential supervisors, directors of specialized programs, etc.
  • Approach potential supervisors in parallel with submitting an application
  • Strong research potential is important, especially for Ph.D.
    try to build up credentials (project courses, USRAs, etc.)

Typical application checklist

  • Statement of research interests
  • Reference letters (at least 2) from professors knowledgeable about your mathematical abilities
    • invest time in allowing professors to get to know you so that they can provide meaningful information!
  • GRE (Graduate Record Examinations) scores (for the US)
  • Transcripts
  • Application fee

Finances

  • Total pay is on the order of $28 - $30K domestic, international PhD, more for international MSc
  • tuition and fees \(\approx\) $7K domestic
  • slightly higher with scholarships
  • in flux!

Scholarships

  • NSERC CGS-M www.nserc.ca
    • Canadian citizens/PRs
    • A- (80%) average minimum in each of last 2 years
    • approx. $17,500
  • OGS osap.gov.on.ca
    • Canadian citizens/PRs
    • A- (80%) average minimum in each of last 2 years
    • approx. $15,000 ($5,000 per term)
  • MITACS, Commonwealth, Canada-US Fulbright, French Embassy, etc.
  • Universities often top-up these awards

Important deadlines

  • November to January grad school application deadlines
  • February 1 application deadline at McMaster (sooner is better)
  • December 1 NSERC CGS-M (direct to NSERC web site)
  • no deadline for OGS (part of grad school application)
  • GRE registration deadline for subject test is early September

Supervisor/student relationship

  • Super important, especially for Ph.D.
  • Compatible research area and compatible personality/work style/etc.
  • Engage with potential supervisors, and talk to current and/or past students (in private!)
  • How to contact a supervisor
    • Know what they do (check web page, read papers, etc.)
    • Explain how your interests/background/skills/experience match with their research program
    • Don’t spam

Supervisors (continued)

  • Supervisor not required for application, but required for admission to some programs
  • You will be accepted if:
    • Your application stands out or
    • A supervisor picks your application out of the pile

Additional Resources