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DESCARTES Scholars Program

Data-Enabled Science and Computational Analysis
Research, Training and Education for Students

for Undergradaute Applied Math Majors

The DESCARTES Scholars Program is a four-year research, training, and education program for undergraduate applied math majors, featuring the following:

  • Stipend for research activities for three summers starting after the Scholar's first year,
  • Research during the academic year with one of the faculty mentors,
  • Senior capstone project containing original research and/or new software that will be disseminated publicly,
  • Career development opportunities in computational and data-enabled science.

Sample schedule of math courses for students majoring in Applied Mathematical Sciences with emphasis in Computational and Data-Enabled Science.

  Year Fall Semester Spring Semester  
Math 21: Calculus I
Math 22: Calculus II
Math 50: Introduction to Matlab
Math 23: Vector Calculus
Math 32: Probability and Statistics
Math 52: Introduction to R*
Math 24: Linear Algebra and Diff. Eq.
Math 110: Topics in Scientific Computing*
Math 101: Real Analysis
Math 131: Numerical Analysis I
Math 141: Linear Algebra
Math 132: Numerical Analysis II
Math 146: Numerical Linear Algebra*
Math 155: Cloud Computing*
Math 125: Intermediate Diff. Eq.
Math 140: Optimization
Math 181: Stochastic Processes
Math 122: Complex Variables
Math 126: Partial Diff. Eq.
Math 150: Mathematical Modeling

Courses listed above that are marked with a * indicate a new course to be developed.

Eligibility. Applicants must be

  • First-year undergraduate students;
  • Declared Applied Math majors by the start of Spring Semester, 2015; and
  • U.S. citizens or permanent residents of the United States or its possessions

Application. Download an application here. Send completed application form to Applications are due 5:00 p.m. on Friday, Oct. 31, 2014.

Contacts. For further information, email
Director: Prof. Arnold Kim (
Co-Director: Prof. Roummel Marcia (

This program is supported by NSF Grant DMS-1331109. Any opinions, findings and conclusions or recommendations expressed in the publications supported by this grant are those of the author(s) and do not necessarily reflect the views of the NSF.