录取要求

The program requires least three semesters of Calculus (including multivariate calculus), as well aslinear algebra. Experience with programming in a high-level language (e.g., Java, C, C++, Fortran, Python) as well as data structures and algorithms, equivalent to a first-year sequence in computer science, is also required. It is highly desirable that applicants have undergraduate major or significant experience in mathematics, a quantitative science or engineering, or economics.

The deadline for application to the program is March 1st for the fall semester. The program admits students both on a full-time and on a part-time basis. The application process takes place online via the Graduate School of Arts and Sciences; please visit the Graduate School Admissions site.

申请材料清单

The Graduate School of Arts and Science requires all applicants for degree programs to apply on-line using EMBARK. For further information, please go to the GSAS admissions web site to apply on-line. The GSAS web site also has instructions and links to the most frequently asked questions and verification about receipt of applications.

The rules and regulations governing admissions to NYU's Graduate School of Arts and Science must be met by all applicants seeking admission to graduate study in mathematics.

All applicants must have an accredited baccalaureate degree or its equivalent. Applicants in their last semester of undergraduate study must graduate before they begin their graduate work at NYU.

An official transcript from all previously attended institutions (undergraduate, graduate, and continuing educational programs) must be uploaded using the online application system.

A student must provide three letters of recommendation (except non-degree). It is strongly recommended that at least two of these letters be from faculty with whom the applicant took a mathematics or other science course. Letters must be submitted using the online application system.

General GRE (Graduate Record Examination) scores are required of all applicants (except non-degree); applicants for the Ph.D. program must also provide the subject GRE score, preferably in mathematics, but accepted in other relevant sciences.

Applicants whose native language is not English must submit a TOEFL (Test of English as a Foreign Language) score; scores of less than 600 (250 for the computer-based test; 100 for the internet-based test) are generally not recommended for admission. This requirement may be waived for an applicant with an accredited degree from an institution where English was the language of instruction. IELTS scores are not accepted by the Graduate School of Arts and Sciences in place of the TOEFL.

List code 2596 for the NYU Graduate School of Arts and Science in your request to the Educational Testing Service for forwarding official GRE and TOEFL scores. The departmental code for the GRE is 0703; for the TOEFL it is 72.

专业介绍

Scientific computing is an indispensable part of almost all scientific investigation and technological development at universities, government laboratories, and within the private sector. Typically a scientific computing team consists of several people trained in some branch of mathematics, science, statistics, or engineering. What is often lacking is expertise in modern computing tools such as visualization, modern programming paradigms, and high performance computing. The master's program in scientific computing aims to satisfy these needs, without omitting basic training in numerical analysis and computer science. Many graduates of this program work at technologically advanced institutions, especially in research and development, where their skills and experience complement those without interdisciplinary degrees. The program is also open to students who will go on to pursue doctoral studies in computer science, mathematics, or statistics.

The master's program in scientific computing focuses on the mathematics and computer science related to advanced computer modeling and simulation. The program is similar in structure to terminal master's programs in engineering, combining classroom training with practical experience. The coursework ranges from foundational mathematics and fundamental algorithms to such practical topics as data visualization and software tools. Electives encourage the exploration of specific application areas such as mathematical and statistical finance, applications of machine learning, fluid mechanics, finite element methods, and biomedical modeling. The program culminates in a master's project, which serves to integrate the classroom material.

课程设置

• MATH-GA 2010, Numerical Methods I,
• MATH-GA 2020, Numerical Methods II,
• MATH-GA 2701, Methods of Applied Mathematics,
• MATH-GA 2490, Partial Differential Equations I,
• MATH-GA 2702, Fluid Dynamics,
• MATH-GA 2962, Mathematical Statistics,
• MATH-GA 2704, Applied Stochastic Analysis,
• DS-GA 1002, Statistical and Mathematical Methods;
• CSCI-GA 1170, Fundamental Algorithms,
• CSCI-GA 2110, Programming Languages
• CSCI-GA 2246, Open Source Tools,
• CSCI-GA 2270, Computer Graphics,
• CSCI-GA 2565, Machine Learning, CSCI-GA 2566, Foundations of Machine Learning,
• DS-GA 1001, Introduction to Data Science,
• S-GA 1003, Machine Learning and Computational Statistics,
• DS-GA 1004, Big Data;