Program Objectives and Description
Computational Science is the field of study concerned with constructing mathematical models and quantitative analysis techniques and using computers to analyze and solve scientific problems. In practical use, it is typically the application of computer simulation and other forms of computation to problems in various scientific disciplines. Computational Science has become critical to scientific leadership, economic competitiveness, and national security.
CWU will offer this masters program with the aim to prepare students for professional computational science careers or to pursue a doctoral degree. The computational core of the program will be materialized in by modular and flexible inter-departmental collaboration. Professional computational scientists possess a broad grounding in computing related areas, mathematics, and sophistication in their area of concentration. The program promotes the expansion and strengthening of the collaborative educational and research efforts across the College of the Sciences.
The program will be entirely delivered at the CWU Ellensburg campus and will be a combination of traditional courses, seminar, and research work amounting to a total of 45 credits. Regular attendance to research seminars offered in the various departments involved in the program will also be required. Students will complete 21 credits of core course work in computer science and 5 credits of thesis/capstone project work. Additionally, students will complete at least 8 credits of elective coursework in their selected area(s) of expertise. A full-time student has to take at least 10 credits per quarter. A typical break down for a student in the program would be:
- 21 credits core courses
- 19 credit electives, including graduate research
- 5 credits master’s thesis/project
Students will have to complete the core course work of the program:
- Advanced data structures and algorithms
- High-performance computing
- Advanced algorithms for scientific computing
- Computational Statistics
- Scientific Computing
Since research is a key part of student development in this program, the rest of the work in the master of computational science will focus on a (year-long) research project with an advisor in their selected area of expertise. Alternatively, and with the approval of the Computational Science Program Committee, students will have the option to do research, or work on a project in partner of the program. Regular attendance to research seminars will also be required.
Students who are part of the program will be required to do a master’s thesis or a project at the end of the program. The two alternatives (thesis or project) mean that students may choose between a research and a professional orientation.
The Thesis/Project Committee, having at least three members, will be chaired by a graduate faculty from the Computer Science Department. All actual professors from the Computer Science Department have the Graduate Faculty status: Dr. Boris Kovalerchuk and Dr. Razvan Andonie. Interdisciplinary membership in the graduate committee is strongly recommended. For this program, the graduate committee will be generally interdisciplinary.
Each core course will be offered one time per year. The elective courses will be generally offered every other year. Students will specialize in one of the following application areas:
- Biological and environmental sciences
- Computer Science
To be considered, an applicants to this graduate program must have been awarded (or about to be awarded) a 4-year bachelor’s degree, with a 3.25 or higher.
The target audience will consist primarily of computer science graduates (i.e., graduates with a major in computer science). We also target graduates with a minor in computer science and a major in one of the application domains (mathematics, biology, chemistry, physics, and geology). On a case by case basis, graduates from the application domains, without a minor in computer science, may be also accepted, if they have enough credits from computer related courses (computer programming, algorithms and data structures, and computer organization).