Since my work spans ecology, evolution, epidemiology, mathematics, statistics, and computation, my ideal prospective student/postdoc knows something about all of those topics. You shouldn’t be discouraged if you don’t know all that stuff yet (I didn’t when I started!), but knowing something about some of it will definitely encourage me to accept you as a student because:
I won’t have to teach you the basics before you can start research
you will have demonstrated some initiative (I don’t like to hear “I’m fascinated by (math/stats/computation/ecology/epidemiology), but I have never made any effort to learn about it” …). If you are switching from another subfield of math or biology, I need to know that you’re serious.
My ‘lab’ size is approximately 1-2 undergraduates, 1-2 master’s students, 1-2 PhD students, maybe a postdoc. (I take relatively few undergraduate and master’s students because I don’t need people to do grunt-work/have to invest a lot in each student.)
I would expect to hear from prospective graduate students sometime May-October for admission the following September, and prospective undergraduate thesis students in March-April for thesis projects starting the following September.
I like prospective students to have some idea what topics they would like to work on. More detailed proposals are welcome, but in my experience most incoming students have a hard time identifying a good, feasible project. Check the ideas page and some of my recent papers for general areas of interest.
I list McMaster course equivalents for each topic below. If you’re not from McMaster and want further details about the contents of these courses, you can look them up in the McMaster undergraduate calendar or the math & stats course outlines.