The enormous progress in computational technology has generated a new methodology for learning and advancing the traditional sciences such as physics, chemistry, and biology. Computational science combines the application of numerical methods, models, and algorithms in the context of solving problems that are intractable by traditional methods. It is distinct from computer science, which is the study of computers and computation, and it is different from theory and experiment, the traditional forms of science, in that it seeks to gain understanding principally through the analysis of mathematical models.

The goal of the interdisciplinary computational science concentration is to provide an opportunity for students to learn about the interplay between science and computation. The concentration is especially suitable for undergraduate students majoring in the sciences, mathematics, or computer science. Students completing this concentration may enter graduate programs in either their majors or in newly created interdisciplinary graduate programs in computational science, and be well prepared to go into industry.

• Computational Science Faculty
• Requirements
• Research project
• Advising
• Typical Course Schedules
  • Biology
  • Chemistry
  • Computer Science
  • Mathematics
  • Physics

• Jerry Breecher, parallel computing, software and hardware performance optimization
• Arthur Chou, algorithms, complexity, bioinformatics
• Harvey Gould, computer simulation, statistical mechanics
• Fred Green, theory of computation, structural complexity
• Li Han, robotics, computer simulation, bioinformatics
• David Hibbett, molecular evolution, phylogenetic analysis
• Shuanghong Huo, biomolecular interactions and dynamics
• Todd Livdahl, population biology, biostatistics
• Natalia Sternberg, applied mathematics, scientific computing

The program is open to students majoring in the natural sciences, mathematics, or computer science. The requirements for the program vary depending on the student's major and interests, but all students are required to complete the following (or equivalent):

1. Computer Science 101 (or the equivalent), 102 (programming)
2. Mathematics 120, 121 or 124, 125 (one year of calculus)
3. One year of chemistry or physics
4. Physics 127, Computer simulation laboratory (Physics 127 can be substituted for CSCI 101)

Four additional courses from a list of recommended courses (see the following), with the approval of the program faculty.

1. Biology 254, Molecular evolution and systematics
2. Biology 280, Biostatistics and computer applications
3. Chemistry 242, Nuclear chemistry
4. Chemistry 264, Biophysical Chemistry
5. Chemistry 270, Quantum chemistry
6. Chemistry 275, Protein chemistry
7. Computer Science 160, Data structures and algorithms
8. Computer Science 210, Artificial intelligence
9. Mathematics 114, Discrete mathematics
10. Mathematics 212, Numerical analysis
11. Mathematics 217, Probability and statistics
12. Physics 150, Statistical and Thermal Physics
13. Physics 217, Advanced computer simulation laboratory

Advising

Because of the sequential nature of many of the requirements and the relatively large number of major requirements for students in the concentration, students are encouraged to plan early and carefully. Students' choice of advanced courses must be approved by the concentration faculty.

Typical Course Schedules
In the following we list typical course schedules that might be taken by students majoring in biology, chemistry, computer science, mathematics, and physics. Students in the Environmental Science and Policy Program are also able to fulfill the requirements for the computational science concentration. Only five perspective courses and the VE are listed because the FA and science perspective are fulfilled by required courses.

Sample course schedule for a biology major.

Sample course schedule for a chemistry major.

Sample course schedule for a computer science major.

Sample course schedule for a mathematics major.

Sample course schedule for a physics major.

Please send comments, questions and suggestions to hgould@clarku.edu