Computational Sciences and Informatics Ph.D.

The computational sciences and informatics (CSI) doctoral program addresses the role of computation in science, mathematics, and engineering, and is designed around a core of advanced computer technology courses. "Computational sciences" is defined as the systematic development and application of computing systems and computational solution techniques to models of scientific and engineering phenomena. "Informatics" 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. Computing is now part of a triad, along with theory and experimentation that serves as a means of investigation and it provides insight and leads to understanding that, in many cases, theory or experimentation cannot. The close relationship of the CSI doctoral program to the research and development activities in federal laboratories, scientific institutions, and high-technology firms affords students opportunities for continuing or new employment. Scheduled courses and sequences accommodate part-time students, with most courses meeting once per week in the late afternoon or early evening.

Each student completing the CSI doctoral program receives extensive training in a selected area of scientific concentration along with a broad background in modern computational techniques. Graduates from this program are qualified to pursue careers in academia, private industry, and government laboratories and agencies. The CSI doctoral program provides interdisciplinary research opportunities spanning, but not limited to, the following specialty areas: atmospheric transport and dispersion; bioinformatics and computational biology; climate dynamics and global change; computational chemistry; computational finance; computational fluid dynamics; computational intelligence and knowledge mining; computational mathematics; computational neuroscience; computational physics; computational statistics; computer design of materials; Earth observing and remote sensing; and space sciences and computational astrophysics.

Degree Requirements

The program emphasizes three intellectual elements: common computational science topics; computationally intensive courses in specific areas of interest; and doctoral research. The course work is divided as follows:

• The common computational core courses: CSI 700, 701, 703, and 710
• The scientific core courses in one of the areas of concentration
• Scientific electives from specialty courses in the area of concentration, or individualized study based on professional experience and research
• General electives
• Three credits of colloquia or seminars, with at least one credit of CSI 899

The program requires 72 credits beyond the baccalaureate degree, with a minimum of 48 credits in course work, and 24 credits of dissertation research. For those holding master's degrees, the 72 required credits may be reduced by up to 30 credits, depending on graduate courses completed. At the end of the semester when course work is completed, the student must form a doctoral committee, which will write the student's candidacy examination. The examination includes written, oral, and computational components. Upon passing the candidacy examination and submitting an acceptable dissertation proposal, the student is advanced to doctoral candidacy.

Students are encouraged to apply their knowledge to a broad range of natural science problems using computational skills and techniques missing from the more traditional degree programs in science and mathematics. Note that research opportunities are not limited to the listed areas, and many opportunities exist to create new areas of interdisciplinary research that would be difficult to accommodate within a traditional doctoral program. Students are to consult with their advisors to prepare their specific plans of study. Complete information regarding the curriculum requirements (including electives) for each of the areas of concentration is available at the School of Computational Sciences web site www.scs.gmu.edu. In addition to the common core of CSI 700, 701, 703, and 710, required scientific core courses for the specific areas of concentration are indicated in the following list:

Atmospheric Transport and Dispersion: two of CSI 655, CLIM 711, EOS 854

Computational Chemistry: CSI 711, 713, 782 and 783

Computational Finance: STAT 652 and 656; CSI 771 and 776; and two courses in finance

Computational Fluid Dynamics: CSI 721, 722, and 780; CSI 783 or 784; and CSI 785 or PHYS 513

Computational Intelligence and Knowledge Mining: CSI 771, 773, 777, and 873

Computational Mathematics: CSI 740; MATH 677 or 678; two additional math courses

Computational Physics: CSI 780; CSI 783 or 784; CSI 785 or PHYS 513; and one of CSI 782, 783, 784, 888, or PHYS 705

Computational Statistics: CSI 771 or 773; CSI 778; CSI 876 or 877; CSI 972 and 973

Computer Design of Materials: CSI 685 or 687; CSI 780 and 783; CSI 782 or 786; and CSI 787 or 986

Earth Observing and Remote Sensing: CSI 750, EOS 753, 754, and 757

High-Performance Computing: CSI 702, 909, and one of CSI 721, 761, 788, or EOS 754

Space Sciences and Computational Astrophysics: CSI 661 and 784; CSI 781 or 782; CSI 785 or PHYS 513; and one of CSI 721, 761, or 788

Students may also pursue interdisciplinary research that combines the areas of concentration listed above with each other and also with computational neuroscience, climate dynamics, and bioinformatics, which are now separate Ph.D. programs within SCS.