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The B.S. in Computational and Applied Mathematics (CAM) at the University of Chicago provides a rigorous foundation in applied mathematics and computational techniques. The program emphasizes real-world applications of differential equations, optimization, numerical analysis, and modeling, while fostering strong programming and problem-solving skills.
It is ideal for students interested in research, engineering, finance, or data-intensive fields.
Core Curriculum Components
Mathematics Foundation
MATH 18300/18400/18500: Mathematical Methods for Physical Sciences (or honors equivalent)
MATH 19620/20000: Linear Algebra
MATH 20310: Analysis in Rn or MATH 20500: Real Analysis I
MATH 27300: Basic Theory of Ordinary Differential Equations
Computational & Applied Core
CAAM 20000: Computational and Applied Mathematics I – Introduction to scientific computing and numerical methods
CAAM 20100: Computational and Applied Mathematics II – Applications of linear algebra and modeling techniques
CAAM 21000: Optimization and Computational Linear Algebra
CAAM 21500: Applied Partial Differential Equations
CAAM 28000: Mathematical Modeling and Simulation
Programming & Data Foundations
CMSC 12100/12200: Computer Science with Applications I & II (Python and computational tools)
CMSC 27100: Discrete Mathematics
CMSC 27500: Algorithms and Data Structures (recommended for theory-oriented students)
Capstone Requirement
CAAM 29000: Capstone Project in Applied Mathematics
A significant modeling or simulation project, often tied to real-world applications or research problems in physics, finance, engineering, or public policy.
UChicago emphasizes hands-on, interdisciplinary exploration. CAM students have multiple opportunities to apply theory through research, internships, modeling competitions, and lab-based coursework.
Research Opportunities
Students are encouraged to engage in research via:
College Research Opportunities (CROC)
Research Experiences for Undergraduates (REU) in Math, Physics, or Data Science
UChicago Applied Math Lab – interdisciplinary work in areas like fluid mechanics, imaging, and nonlinear dynamics
Collaborations with Argonne National Laboratory, especially in computational science and machine learning
Capstone Projects
Students complete team-based or individual projects such as:
Simulating atmospheric turbulence
Building predictive models for stock volatility
Modeling population dynamics or epidemiological spread
Applying PDEs to traffic flow optimization
Competitions & Challenges
SIAM Modeling Challenge
Putnam Mathematics Competition
Data Science Bowl
HackArts and HackTheMidway
These platforms foster innovation and critical thinking under time and resource constraints.
Internships & Industry Exposure
Students gain practical experience through internships in:
Finance: DRW, Citadel, Goldman Sachs
Tech: Microsoft, Amazon, Google Research
Science & Engineering: Fermilab, NASA, Boeing
Consulting & Analytics: McKinsey, BCG Gamma, Jane Street
Graduates of UChicago’s CAM program are known for their technical depth, mathematical rigor, and applied problem-solving skills. They are well-positioned for elite graduate programs or technical careers requiring a deep understanding of both computation and real-world systems.
Career Progression Paths
Applied Mathematician → Principal Scientist → Director of Modeling
Software Engineer → Computational Systems Lead → CTO
Data Analyst → Machine Learning Engineer → Head of Data Science
Quantitative Analyst → Portfolio Manager → Chief Investment Officer
Research Assistant → PhD Candidate → Professor / Industry Researcher
Graduate Study Pathways
CAM students are well-prepared for:
PhD in Applied Mathematics, Scientific Computing, or Computational Physics
Master’s in Data Science, Machine Learning, or Operations Research
Joint programs in Computational Biology, Finance, or Engineering
Deadline details: The application deadline is 11:59 p.m. in the applicant's local time zone on the date listed for each application program. Don't panic if you have difficulty submitting the application and it goes through after 11:59 p.m. We want to review your application, and will not disqualify you based on the timestamp.SAT/ACT Update: Submitting an SAT or ACT is optional and not required for admission. In addition to being test-optional, UChicago practices a “No Harm” policy for application review when considering SAT or ACT scores. Any SAT or ACT score submitted will only be used in review if it will positively affect an applicant’s chance of admission.SAT/ACT Score reporting: Students submitting SAT or ACT scores may share either official or self-reported scores. Students sharing self-reported scores will not be required to submit official score reports unless they are admitted and choose to enroll.English language Proficiency: The University of Chicago requires strong English proficiency for admission. You may submit any English test scores that best reflect your ability, though they are optional if your application already demonstrates mastery of the language. Self-reported scores are accepted and only need official confirmation if you enroll. Please note: UChicago does not offer an ESL program for admitted students.Recommendations: School Report- Required, Mid Year Report- Required, Final Report- Required, Teacher Evaluation(s): 2 Required, 1 Optional, Other Evaluation(s): 0 Required, 3 Optional.Writing Requirements: UChicago Writing Supplement – 2 Required Essays Submit both essays via the Common Application. UChicago is known for its unique and thought-provoking essay questions. These essays are your chance to share your personality, interests, and goals—whether serious, playful, or creative. Each year, we crowdsource topics from our students, resulting in hundreds of engaging and sometimes quirky prompts. Learn more about current and past essay topics on our website.Graduates of UChicago’s Bachelor of Science in Computational and Applied Mathematics (CAM) are highly analytical problem-solvers equipped with the mathematicalalgorithmicand modeling tools necessary to tackle real-world challenges in scienceengineeringfinanceand technologyTheir ability to bridge theory and computation makes them valuable across industries where datamodelingand simulation are central to innovation and decision-makingTechnology & Engineering
Scientific Computing Specialist: Developing simulations and numerical models for engineering and physics applicationsSoftware Developer (Quantitative Focus): Writing optimized code for computation-heavy environmentsComputational Scientist: Working in research labs to model fluid dynamicsstructural mechanicsor materials scienceHigh-Performance Computing Engineer: Building scalable computing systems for research and industryFinance & Data Science
Quantitative Analyst (Quant): Modeling financial markets using PDEsstochastic calculusand optimizationRisk Analyst: Applying simulations and probabilistic modeling to evaluate financial riskData Scientist: Leveraging advanced statistical and computational techniques to extract insightsAlgorithmic Trader: Using mathematical models to develop automated trading strategiesAIMachine Learning & Optimization
Machine Learning Engineer: Applying numerical linear algebra and optimization to build predictive modelsOperations Research Analyst: Solving logistical and supply chain problems using mathematical programmingAI Research Scientist: Developing foundational models using computational methods and differential equationsOptimization Engineer: Creating models to improve system performance across industriesResearch & Academia
Computational Mathematician: Pursuing research in numerical analysisapplied PDEsand mathematical modelingPhD Candidate: In applied mathstatisticscomputer scienceor computational biologyAcademic Research Assistant: Supporting cutting-edge research in physicsneuroscienceclimate modelingor economicsEmerging & Interdisciplinary Roles
Biomedical Modeler: Simulating biological processes and disease spread using differential equationsClimate Data Analyst: Modeling and forecasting environmental systems with high-dimensional dataCryptography & Security Analyst: Applying mathematical methods to secure systems
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