Some students enter directly from undergraduate programs, but most have had some work experience between their undergraduate degree and REM. 

Relevant disciplines of undergraduate training or experience include fields such as biology, engineering, chemistry, forestry, and geology, as well as business administration, economics, geography, planning, and a variety of social sciences. 

Some courses at SFU are scheduled in the evenings or for week-long blocks. 

The optional Co-operative Education Program allows students to work in a private organization or a resource management agency to gain first-hand experience while obtaining their degree.

Students complete a research project on a topic involving more than one traditional discipline. Students also become familiar with various quantitative methods of analysis and aid in decision-making. 

The Master of Resource Management is one degree with three streams, and all three streams require students to bring original research to the oral defence. 

The Project is less research intensive than a Thesis, but it is not a course-based master's.

Applicants apply to the Master's program but do not select the stream. The decision about which stream is something you will discuss with your supervisor, and it is a joint decision. 

Students are able to switch streams, provided it's done in the first term.

• Unofficial transcripts
• CV
• Three reference letters
• English proficiency test scores
• Passport

Applicants are normally required to hold an undergraduate degree in a related field with a minimum of 3.0 GPA on SFU’s 4.33 scale (B average or 70%). 

Applications from students with other degrees or with equivalent professional training and experience will also be considered.

Applicants to the School of Resource and Environmental Management must have completed an undergraduate course in parametric and nonparametric statistics. 

It is expected that new students will have acquired and be familiar with the following concepts/methods prior to entry into the School:

• describing distributions graphically and quantitatively (e.g. mean, median, standard deviation)
   
• basic concepts of statistical inference (e.g. calculating test statistics and comparing p-values with an alpha value)
   
• basic inferential tests (t-tests, simple ANOVA, chi-square)
   
• simple linear regression and correlation.

Entry-level undergraduate statistics and data analysis courses normally cover these concepts. You will be asked on your application to explicitly state that you have completed a University-level statistics course.