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I am close to finishing a degree in a combined program in computer science and physics, and I am thinking of applying to graduate school in environmental modelling, ideally with a strong mathematical and computational focus.
My overall GPA seems to be respectable, 3.72 (if I'm doing the conversion correctly). However, I have done much better in computer science courses (3.96) and worse in math (3.51) and physics (3.58).
The problem is that many of the grad programs I'm interested in are in math departments, and I fear that the low math GPA will exclude me from top programs. I should note that part of the reason for the math marks is that I took mostly honours courses, but I worry that admissions committees will not be able to tell (the course names don't always indicate this). I have, however, taken several courses in mathematical methods (both under computer science and math departments) and done very well, and am also taking a math-heavy graduate course in machine learning.
I have extended my degree by a semester to do a math minor, but unfortunately most of my marks for this will not be out by the time I apply for grad programs. I plan to study quite a bit for the GRE Math Subject Exam.
I have research experience in mathematical biology as well as currently working on an undergraduate thesis in environmental modelling. I will hopefully have one or two publications related to this research by the time I apply for schools.
How can I tailor my applications to have a good chance of getting into applied math programs? Will they care about my strong computer science marks, or my marks in specific courses? Should I try instead for computer science programs and go from there?