Master of Engineering (MEng) in Civil Engineering

The program information below was valid for the winter 2017 term (January 1, 2017 - April 30, 2017). This is the archived version; the most up-to-date program information is available through the current Graduate Studies Academic Calendar.

The Graduate Studies Academic Calendar is updated 3 times per year, at the start of each academic term (January 1, May 1, September 1). Graduate Studies Academic Calendars from previous terms can be found in the archives.

• Admit term(s) 
  • Fall
• Delivery mode 
  • On-campus
• Program type 
  • Master's
  • Professional
• Registration option(s) 
  • Full-time
  • Part-time
• Study option(s) 
  • Coursework
• Additional program information 
  • The University of Waterloo does not provide funding for MEng in Civil Engineering students, and the candidates are expected to be self-supporting.
    
    *Section updated January 11, 2017

• Minimum requirements 
  • An Honours Bachelor's degree (or equivalent) with a 75% standing.
• Application materials 
  • Résumé
  • Supplementary information form
  • Transcript(s)
• References 
  • Number of references:  3
  • Type of references: 

    at least 2 must normally be from academic sources.

• English language proficiency (ELP) (if applicable)

Coursework option:

Graduate Academic Integrity Module (Graduate AIM)

Courses 

• Students must complete 8 one-term graduate level courses (0.50 unit weight) taken from the 500, 600 and 700 series courses (or courses acceptable for graduate credit) and 1 technical/professional writing course for engineers (EMLS 602R Scholarly Writing in English).
• A maximum of 2 500 level courses may be counted for credit.
• The candidate must obtain a pass in all courses credited to their program, with a minimum overall average of 70% (a grade of less than 65% in any course counts as a failure).
• At least half of the courses used for credit must normally be Faculty of Engineering courses.

Link(s) to courses

• Civil Engineering (CIVE) courses

Engineering Data Analysis Graduate Workshop