Stanford University

Overview

The PhD in Computational and Mathematical Engineering (CME) at Stanford University prepares students to become leaders in the development and application of computational and mathematical methods to address complex challenges in engineering and the sciences. This program emphasizes rigorous academic training and research, enabling students to contribute significantly to their fields.

What you'll study

The curriculum blends graduate-level coursework with intensive research training. Students engage with foundational topics and advanced concepts, ultimately focusing on their dissertation work under the mentorship of faculty advisors affiliated with the Institute for Computational and Mathematical Engineering (ICME).

Coursework includes topics such as:

• Imaging with Incomplete Information
• Computational Biology: Structure and Organization of Biomolecules and Cells
• Convex Optimization
• Computational Biology in Four Dimensions
• Computer Graphics: Geometric Modeling & Processing
• Digital Image Processing
• Real Analysis
• Algebraic Topology
• Stochastic Differential Equations
• Finite Element Analysis
• Molecular Simulations

Research and dissertation:

• Conducted under the guidance of an ICME-affiliated faculty member
• Includes participation in seminars, research groups, and scholarly activities within the ICME community
• Dissertation based on original research contributions

Entry requirements

While specific GRE/GMAT scores and GPA thresholds are not mandated, applicants are expected to exhibit strong academic preparation suitable for advanced graduate study in computational and mathematical methods. Prospective students should prepare to submit a Statement of Purpose, letters of recommendation, and academic transcripts as part of the application process.

Career prospects

Graduates of the PhD program in Computational and Mathematical Engineering are well-equipped for diverse career paths in academia, industry, and research institutions. They can pursue roles that involve advanced computational modeling, data analysis, and algorithm development, contributing to innovations across various engineering and scientific disciplines.