School of Computational Sciences
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 many 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 30credits,
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: CSI 655 and 755
Bioinformatics and Computational Biology: CSI 730, 731,
and 732
Climate Dynamics and Global Change: CSI 751, 755, and
852; CSI 752 or 756
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: CSI771,
773, SYST 781, and IT 811
Computational Mathematics: CSI 740; MATH 677 or 678;
two additional math courses
Computational Neuroscience: CSI 639, 734, and 735
Computational Physics: CSI 780; CSI 783 or 784; CSI785
or PHYS 513; and one of CSI 782, 783, 784, 888, or PHYS 705
Computational Statistics: CSI 771 or 773; CSI 778; CSI876
or 877; CSI 972 and CSI 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, 753, 754,
and 757
High-Performance Computing: CSI 709, 909, and one of
CSI 721, 754, 761, or 788
Space Sciences and Computational Astrophysics: CSI 661
and 780; CSI 783 or 784; CSI 785 or PHYS 513; and one of CSI 721, 761, or 788
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