Requirements
Your application should demonstrate that you will benefit from the following curriculum. The minimal prerequisites for the master’s program are a solid background in multi-variate calculus, linear/matrix algebra, and elementary probability and statistics.
The deadline to submit applications for Fall 2024 admission, along with all necessary documentation, was January 31, 2024. The online application will begin accepting applications for Fall 2025 admission in early Fall 2024.
Curriculum
The MCAM program consists of at least nine graduate level courses related to Computational and Applied Mathematics, as described below. All course programs must be approved with the signatures of the student’s academic advisers. Students can select one of the following tracks. Each track includes a sequence of three courses.
(i) Computational Mathematics Track:
• Mathematical Computation I: Matrix Computation (CAAM 30900)
or Applied Linear Algebra (CAAM 31430)
• Mathematical Computation II: Optimization (CAAM 31020 or CAAM 31015)
• Machine Learning (CAAM 37710) or Applied Approximation Theory (CAAM 31050)
(ii) Applied Analysis and Modeling Track:
• Applied Dynamical Systems (CAAM 31410)
or Applied Analysis (CAAM 31440)
• Applied Functional Analysis (CAAM 31210)
• Partial Differential Equations (CAAM 31220)
Students will complete three additional courses of their choice. They may select from the track they did not pursue above or from other courses offered as part of the CAM graduate programs. Some courses may have prerequisite requirements or require instructor consent in order to enroll. Recent course offerings have included (but are not limited to) the list below.
o Scientific Computing with Python
o Applied Partial Differential Equations
o Applied Fourier Analysis
o Inverse Problems and Data Assimilation
o Monte Carlo Simulation
o Modern Applied Optimization
o Mathematical Computation III: Numerical Methods for PDEs
o Numerical Methods for Stochastic Differential Equations
o Stochastic Processes in Gene Regulation
o Variational Methods in Image Processing
o Inverse Problems and Imaging
o Topological Data Analysis
o Topics in Random Matrix Theory
o Stochastic Calculus
o Measure Theoretic Probability (sequence)
o Modern Inference
Click here for selected course descriptions.
For the remaining three courses, students can select from the above lists or from graduate-level courses related to CAM offered through the Physical Science Division, TTIC, or the Booth Business School.
Students are required to complete the online Responsible Conduct of Research (RCR) training through the CITI program by the end of their first quarter of enrollment. Students are expected to maintain good academic standing throughout their graduate career. The MCAM program may impose restrictions or take other actions (including placing a student on Academic Probation) if a student fails to remain in good standing.
Students with questions may contact Jonathan Rodriguez (Student Affairs Administrator), Bahareh Lampert (Dean of Students in the Physical Sciences Division), or Amanda Young (Associate Director, Graduate Student Affairs) in UChicagoGRAD.
Master’s Thesis Option
Students who wish to do so can pursue the option of a master’s degree with thesis. Students who pursue this option are required to:
(i) complete the above requirements; and
(ii) write and defend a master’s thesis under the guidance of a CAM advisor.
The option without master’s thesis may be completed in nine months (three full-time quarters) or more. The option with a master’s thesis may be completed in 15 months (four full-time quarters, excluding summer) or more. Both options can extend up to two academic years. Students interested in pursuing a PhD program afterwards are encouraged to consider the option with thesis.