Key takeaways
- 2 year program
- tuition fee $120,000 in total, 6 quarters
- rigorous course works concentrated in computation and financial engineering
- bridge to PhD
Program
PROGRAM | TYPE | ENTRY QUARTER | APPLICATION DEADLINE | DECISION DATE |
---|---|---|---|---|
PhD* | All Applicants | Autumn Quarter 2024-25 | November 30th, 2023 | End of February 2024 |
MS* | All Applicants | Autumn Quarter 2024-25 | January 31st, 2024 | End of March 2024 |
admission only in autumn quarter each year
PhD program also provided
- Applications are for autumn quarter admissions only
- Applicants must apply to a specific track (for example, “computational geosciences”) in the application under the academic interest field; the application is only considered for that specific track
- Application can be submitted to one track only (it is Stanford policy that an applicant can submit one application only for admission to a particular term)
- All tracks are designed to be completed in two years
- C.V. is strongly recommended
Fees
Total Units | Quarterly Tuition |
---|---|
8-10 units | $13,040 |
11-18 units | $20,058 |
each Graduate Engineering unit above 18 | $1,337 per unit |
1-7 units (Summer only) | $1,304 per unit |
Prerequisites/requirements
- transcripts
- GRE - for Fall 2023, not required
- TOEFL
- Scores must be submitted from a test taken within the last 18 months of the application deadline.
Statement of Purpose
Your Statement of Purpose should identify your personal and professional goals. You should also discuss your development to date and your intentions relative to graduate study and life beyond Stanford. The ICME Graduate Admissions Committee reads your statement of purpose with interest because, along with the letters of recommendation, it offers insight into who you are as an individual. Your statement of purpose should not exceed 10MB in either a PDF or Word file.
Letters of Recommendation
Three letters of recommendation are required; at least one letter must come from an academic source, however we recommend two. Please have your recommender write candidly about your qualifications, potential to carry on advanced study in the field specified, intellectual independence, capacity for analytical thinking, ability to organize and express ideas clearly, and potential for teaching. Specific examples–that describe such attributes as motivation, intellect, and maturity–are more useful than generalizations.
- Recommendation letters can be submitted up to one week after the application deadline.
Curriculum
Students must take 45 units in the following areas:
- Foundational (9 units)
- Programming (9 units)
- Finance electives (9 units)
- Data Science electives (12 units)
- Practical component (6 units)
Suggested Specializations
- Financial Mathematics
- Financial Data Science
- Financial Technology
- Financial Markets
- PhD prep
CODE | NAME |
---|---|
https://bulletin.stanford.edu/courses/2196651 | How to learn Mathematics - New ideas from the science of learning |
https://bulletin.stanford.edu/courses/2023541 | Vector Calculus for Engineers |
https://bulletin.stanford.edu/courses/2256201 | Vector Calculus for Engineers, ACE |
https://bulletin.stanford.edu/courses/1043151 | Ordinary Differential Equations for Engineers |
https://bulletin.stanford.edu/courses/2256911 | Ordinary Differential Equations for Engineers, ACE |
https://bulletin.stanford.edu/courses/1043162 | Linear Algebra and Partial Differential Equations for Engineers |
https://bulletin.stanford.edu/courses/2016572 | Introduction to Probability and Statistics for Engineers |
https://bulletin.stanford.edu/courses/2256921 | Introduction to Probability and Statistics for Engineers |
https://bulletin.stanford.edu/courses/2195782 | Introduction to Machine Learning |
https://bulletin.stanford.edu/courses/1056641 | Introduction to Scientific Computing |
https://bulletin.stanford.edu/courses/2226472 | Mathematical Population Biology |
https://bulletin.stanford.edu/courses/2140171 | Introduction to MATLAB |
https://bulletin.stanford.edu/courses/2140581 | Introduction to Scientific Python |
https://bulletin.stanford.edu/courses/2222851 | Human-Centered Design Methods in Data Science |
https://bulletin.stanford.edu/courses/1048651 | Linear Algebra with Application to Engineering Computations |
https://bulletin.stanford.edu/courses/1048663 | Partial Differential Equations in Engineering |
https://bulletin.stanford.edu/courses/1048671 | Introduction to Numerical Methods for Engineering |
https://bulletin.stanford.edu/courses/2226321 | Mathematical Modeling of Biological Systems |
https://bulletin.stanford.edu/courses/2068101 | Software Development for Scientists and Engineers |
https://bulletin.stanford.edu/courses/2120661 | Introduction to parallel computing using MPI, openMP, and CUDA |
https://bulletin.stanford.edu/courses/2206512 | Machine Learning for Computational Engineering. |
https://bulletin.stanford.edu/courses/2226441 | Analytics Accelerator |
https://bulletin.stanford.edu/courses/2234861 | Analytics Accelerator Seminar |
https://bulletin.stanford.edu/courses/2255431 | Applied Data Science |
https://bulletin.stanford.edu/courses/2257921 | Applications of machine learning to electronic markets |
https://bulletin.stanford.edu/courses/2207331 | Foundations of Reinforcement Learning with Applications in Finance |
https://bulletin.stanford.edu/courses/2109902 | Risk Analytics and Management in Finance and Insurance |
https://bulletin.stanford.edu/courses/2164442 | Introduction to Machine Learning |
https://bulletin.stanford.edu/courses/2216121 | Introduction to Quantum Computing and Quantum Algorithms |
https://bulletin.stanford.edu/courses/2170092 | Geometric and Topological Data Analysis |
https://bulletin.stanford.edu/courses/2175151 | Advanced Topics in Scientific Computing with Julia |
https://bulletin.stanford.edu/courses/2084232 | Imaging with Incomplete Information |
https://bulletin.stanford.edu/courses/1038992 | Introduction to Linear Dynamical Systems |
https://bulletin.stanford.edu/courses/2237241 | Advances in Computing with Uncertainties |
https://bulletin.stanford.edu/courses/2159422 | Computational Biology: Structure and Organization of Biomolecules and Cells |
https://bulletin.stanford.edu/courses/2179551 | Computational Modeling in the Cardiovascular System |
https://bulletin.stanford.edu/courses/2042921 | Master’s Research |
https://bulletin.stanford.edu/courses/2146711 | Advanced MATLAB for Scientific Computing |
https://bulletin.stanford.edu/courses/2246981 | Computational Symbolic Mathematics |
https://bulletin.stanford.edu/courses/2170262 | Probability and Stochastic Differential Equations for Applications |
https://bulletin.stanford.edu/courses/2058061 | First Year Seminar Series |
https://bulletin.stanford.edu/courses/2240811 | ICME QUALIFYING EXAMS WORKSHOP |
https://bulletin.stanford.edu/courses/1057521 | Numerical Linear Algebra |
https://bulletin.stanford.edu/courses/1173932 | Partial Differential Equations of Applied Mathematics |
https://bulletin.stanford.edu/courses/2042901 | Discrete Mathematics and Algorithms |
https://bulletin.stanford.edu/courses/1174062 | Computational Methods of Applied Mathematics |
https://bulletin.stanford.edu/courses/1045842 | Optimization |
https://bulletin.stanford.edu/courses/2102132 | Stochastic Methods in Engineering |
https://bulletin.stanford.edu/courses/2145632 | Randomized Algorithms and Probabilistic Analysis |
https://bulletin.stanford.edu/courses/1050963 | Spectral Methods in Computational Physics |
https://bulletin.stanford.edu/courses/2163301 | Distributed Algorithms and Optimization |
https://bulletin.stanford.edu/courses/1033832 | Applied Mathematics in the Chemical and Biological Sciences |
https://bulletin.stanford.edu/courses/1045852 | Optimization Algorithms |
https://bulletin.stanford.edu/courses/2119271 | Model Reduction |
https://bulletin.stanford.edu/courses/2241381 | The ABCs of TQC: An introduction to the mathematics of Topological Quantum Computing |
https://bulletin.stanford.edu/courses/2066522 | Convex Optimization I |
https://bulletin.stanford.edu/courses/2066542 | Convex Optimization II |
https://bulletin.stanford.edu/courses/1050292 | Computational Methods in Fluid Mechanics |
https://bulletin.stanford.edu/courses/2151482 | Computational Biology in Four Dimensions |
https://bulletin.stanford.edu/courses/2151422 | Applied Fourier Analysis and Elements of Modern Signal Processing |
https://bulletin.stanford.edu/courses/2050411 | Curricular Practical Training |
https://bulletin.stanford.edu/courses/2248971 | Ph.D. Research Rotation |
https://bulletin.stanford.edu/courses/2128641 | Special Research Topics in Computational and Mathematical Engineering |
https://bulletin.stanford.edu/courses/2042941 | Ph.D. Research |
https://bulletin.stanford.edu/courses/2058211 | Computational Consulting |
https://bulletin.stanford.edu/courses/2042871 | Departmental Seminar |
https://bulletin.stanford.edu/courses/2075411 | Linear Algebra and Optimization Seminar |
https://bulletin.stanford.edu/courses/2050421 | TGR Project |
https://bulletin.stanford.edu/courses/2050431 | TGR Dissertation |
https://bulletin.stanford.edu/courses/2249122 | WiDS Datathon Independent Study |