Requirements: Scientific Computing
The Scientific Computing Concentration is an interdisciplinary program in the application of computers to scientific inquiry. A longer title for the program might be "Computing within a Scientific Context."
The concentration focuses on four major areas:
- Computer program development, including the construction and implementation of data structures and algorithms
- Mathematical modeling of natural phenomena (including cognitive processes) using quantitative or symbolic computer techniques
- Analysis and visualization of complex data sets, functions and other relationships using the computer
- Computer hardware issues, including the integration of computers with other laboratory apparatus for data acquisition
The overall aim is to prepare the student to use computers in a variety of ways for scientific exploration and discovery.
The concentration in scientific computing requires a total of six courses of Kenyon coursework. SCMP 118 (Introduction to Computer Science) serves as a foundation course for the program, introducing students to programming and other essential ideas of computer science.
Contributory courses have been identified in biology, chemistry, economics, environmental studies, mathematics, political science, physics and statistics. In these courses, computational methods form an essential means for attacking problems of various kinds.
Students in the concentration also take at least one intermediate scientific computing course. These courses have computational methods as their main focus and develop or investigate these methods extensively.
In addition to regular courses that are identified as contributory or intermediate, particular special-topics courses or individual studies in various departments may qualify in one of these two categories. Students who wish to credit such a course toward the concentration in scientific computing should contact the program director at the earliest possible date.
The capstone course of the program is SCMP 401 (Advanced Scientific Computing), a project-oriented, seminar-style course for advanced students.
SCMP 118: Introduction to Programming or PHYS 270: Introduction to Computational Physics
SCMP 401: Scientific Computing Seminar
BIOL 109Y–110Y: Introduction to Experimental Biology
BIOL 328: Global Ecology and Biogeography
CHEM 126: Introductory Chemistry Laboratory II
CHEM 336: Quantum Chemistry
CHEM 341: Instrumental Analysis
CHEM 370: Advanced Lab: Computational Chemistry
CHEM 374: Advanced Lab: Spectroscopy
ECON 205: Introduction to Econometrics
ECON 337: Portfolio Allocation and Asset Pricing
ECON 375: Advanced Econometrics
ENVS 261: Geographic Information Science
PHYS 140: Classical Physics
PHYS 141: First-Year Seminar in Physics
PHYS 146: Introduction to Experimental Physics
PHYS 240, 241: Fields and Spacetime and Laboratory
PHYS 345: Astrophysics and Particles
PHYS 380: Introduction to Electronics
PHYS 381, 382: Projects in Electronics 1, 2
PHYS 385, 386, 387: Advanced Experimental Physics 1, 2, 3
PSCI 280: Political Analysis
PSYC 410: Research Methods in Human Neuroscience
STAT 106: Elements of Statistics
STAT 116: Statistics in Sports
STAT 206: Data Analysis
STAT 216: Nonparametric Statistics
BIOL 230: Computational Genomics
MATH 258: Mathematical Biology
MATH 291: Special Topic: Computational Neuroscience (spring 2021)
MATH 328: Coding Theory and Cryptography
MATH 347: Mathematical Models
MATH 348: Software System Design
MATH 368: Design and Analysis of Algorithms
SCMP 218: Data Structures and Program Design
SCMP 318: Software Development
SCMP 493: Individual Study
STAT 226: Statistical Computing with R
STAT 416: Linear Regression Models