Computational Sciences and Informatics, PhD
Founded in 1992, the program addresses the role of computation in science, mathematics, and engineering, and is designed around the emphases of Computer Modeling and Simulation and of Data Science.
Computational science, focused on modeling and simulation, is defined as the systematic development and application of computing systems and computational solution techniques for modeling and simulation of scientific and engineering phenomena. Informatics, focused on data science, is defined as the systematic development and application of computing systems and computational solution techniques for analyzing data obtained through experiments, modeling, database searches, and instrumentation. The resulting interdisciplinary approach leads to an understanding that traditional theory or experimentation alone cannot provide.
- The strength of this program lies in its ability to foster and promote truly interdisciplinary research that crosses traditional domain boundaries. Each student is presented with exciting opportunities of interdisciplinary research fundamentally different from traditional PhD programs.
- Scheduled courses and sequences accommodate part-time students, with most courses meeting once a week in the late afternoon or early evening.
Review admission and course requirements for this degree:
The close relationship of the PhD to research and development activities in federal laboratories, scientific institutions, and high-technology firms gives graduates opportunities for new employment and professional advancement.
Research and teaching activities associated with the program reflect the recognized role of computation for better understanding of nature as part of a triad with theory and experiment.
Students interested in applying for admission should have a bachelor's degree in computational science, any natural science, mathematics, engineering, or computer science with a minimum GPA of 3.00 in their last 60 credits of study. Applicants to the PhD program should have a mathematics background up to and including differential equations and should also have knowledge of a computer programming language such as C, C++, Fortran, Python, etc. (see also https://science.gmu.eadvising as it is currently labeled)