Data-Enabled Science and Computational Analysis Research, Training and Education for Students (DESCARTES) Program
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.
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 descartes.at.ucmerced.dot.edu. Applications are due 5:00 p.m. on November 15, 2014.
Contacts. For further information, email
Director: Prof. Arnold Kim (adkim.at.ucmerced.dot.edu)
Co-Director: Prof. Roummel Marcia (rmarcia.at.ucmerced.dot.edu).
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.