Princeton University

Overview

The PhD in Applied and Computational Mathematics at Princeton University provides a comprehensive education in the development and application of mathematical methods tailored for science and engineering. This program emphasizes research-driven study, allowing students to collaborate closely with faculty on their chosen areas of interest.

What You'll Study

The curriculum is designed around the research interests of the students, who work in consultation with faculty advisers to select relevant coursework and reading options. The program includes a combination of regular and reading courses tailored to the student's topic areas, culminating in required examinations.

• Topic-area selection: By late October, students will determine specific research topics with the guidance of appointed advisers.
• Adviser-led courses: Students will engage in regular or reading courses across three selected topic areas under the mentorship of their advisers.
• Exams and course requirements: Completion of examinations and coursework is necessary for each of the chosen topic areas.

Examples of Course Themes

• Current Topics in Dynamic Meteorology
• Analytical Techniques in Differential Equations
• Methods and Concepts in Electronic Structure Theory
• Numerical Algorithms for Scientific Computing
• Software Engineering for Scientific Computing
• Mathematical Methods of Engineering Analysis
• Applied Dynamical Systems

Note: For the most accurate information regarding course offerings and specific program requirements, students should consult with their department and adviser team.

Entry Requirements

Candidates interested in applying for the PhD program are typically required to submit online application materials through Princeton's application portal. Prospective students should verify specific entry requirements, including standardized test scores and any prerequisite coursework.

Career Prospects

Graduates of the PhD in Applied and Computational Mathematics are well-prepared for a variety of career paths in academia, industry, and research. With strong analytical and mathematical skills, alumni often pursue roles in scientific research, engineering, data analysis, and advanced mathematical modeling across diverse sectors. The program's emphasis on collaboration and research equips students with the necessary tools to address complex challenges in their fields.