| George Mason University > University Catalog > School of Computational Sciences | |
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School of Computational SciencesWeb: scs.gmu.edu
Graduate ProgramsThe School of Computational Sciences offers the following academic programs:
AdministrationMenas Kafatos, Dean Peter A. Becker, Assistant Dean for Graduate Studies James E. Gentle, Assistant Dean for Faculty Paul S. Schopf, Assistant Dean for Research George E. Taylor, Jr., Assistant Dean for Administration IntroductionThe School of Computational Sciences (SCS) results from the recent merger of the Institute for Computational Sciences and Informatics and the Institute for Biosciences, Bioinformatics, and Biotechnology. This new school serves as the primary academic unit providing scientific and applications content to George Mason's information technology focus. This content includes applications in the biological, physical, mathematical, and data sciences. Along with other units, SCS also contributes to the university's focus on educational and research programs related to the environment. Through its interdisciplinary and multidisciplinary activities, SCS seeks to integrate computation in the sciences, mathematics, and engineering to produce new knowledge and to develop new approaches to the solution of complex problems. SCS maintains extensive facilities on both the Fairfax and Prince William Campuses. FacultyAscoli, Beach, Beall, Becker, Black, Blackwell, Blaisten-Barojas, Boybeyi, Carr, Cebral, Chiu, Cioffi, DelSole, Di, Gentle, Gillevet, Gomez, Grefenstette, Guillory, Huang, Jafri, Ji, Kafatos, Kaufman, Kerschberg, Kinser, Kinter, Kirtman, Klinger, Krishnamurthy, Kwiatkowski, Lieb, Lohner, McKenney, Michalski, Mishin, Jamison, Lin, Olds, Papaconstantopoulos, Qu, Sambruna, Sauer, Satyapal, Schneider, Schopf, Schum, Seto, Shukla, Solka, Straus, Summers, Taylor, Vaisman, Wallin, Wang, Wegman, Weller, Willett, Wong, Wood, C. Yang, R. Yang, W. Yang, Zoltek Academic UnitsThe academic and research activities of the School of Computational Sciences are organized into several units termed programs. The programs are semi-autonomous units with their own faculty and chairs. The current programs are listed below, along with the respective program chairs:
The development of new programs in the future is anticipated as the school continues to evolve in its structure in response to faculty academic and research activities. Course WorkThe School of Computational Sciences offers all course work designated Bioinformatics (BINF) or Computational Sciences and Informatics (CSI) in the "Course Descriptions" chapter of this catalog. Admission RequirementsTo apply, prospective students should forward a completed George Mason graduate application, two transcripts from each college and graduate institution attended, a current resume, and an expanded goals statement to the SCS Graduate Admissions Processing Center. Each doctoral or master's program applicant should also include three letters of recommendation and an official report of scores obtained on the GRE-GEN exam. The GRE-SUB is recommended if it is given in the student's undergraduate major. The GRE requirement for admission to the doctoral programs will be waived if the student holds a master's degree from a U.S. institution. TOEFL scores are also required for all foreign applicants. Note that transcripts originating from foreign countries must be evaluated by a U.S.-recognized agency. Specific additional admission requirements for the various SCS programs are listed below:
Fellowships and assistantships are generally available beginning in the fall semester. Those applying for fellowships and assistantships must submit completed applications by February 1 for fall admission; all other applications for fall admission are due by March 1. Applications for spring admission should be received by November 1 of the preceding year. 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; computa tional 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 RequirementsThe 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 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.
Bioinformatics, Ph.D.Recent advances in molecular biology have produced an avalanche of data, including DNA sequences and genetic maps that cover thousands of genes whose functions are poorly understood or completely unknown. These advances are having a profound effect on the biological sciences and have resulted in the development of the new discipline of bioinformatics. Bioinformatics utilizes computational approaches to analyze patterns in biological data and to create complex models of biological activity, including attempts to elucidate the functions of genes and their interactions in genetic pathways. Widespread social benefits are expected from the exploitation of the wealth of new knowledge concerning the genetic mechanisms of life and related processes. The coming years will see major developments in medicine, functional genomics, and environmental sciences, as well as profound advances in our understanding of the fundamental processes of biology. These benefits are increasingly dependent on the application of advanced information technology to the analysis of biological information. The main objective of the Ph.D. in Bioinformatics program is to train the next generation of computational biologists for careers in academia, industry, and government. The program provides students with an interdisciplinary academic environment, including fundamental biosciences courses as well as core and advanced courses in bioinformatics. In general, course requirements may be completed within the first two years of the program. The program is structured to be accessible to both full-time and part-time students. Degree RequirementsThe curriculum is divided into four areas: 12 credit hours of fundamental biosciences courses; 16 credit hours of core bioinformatics courses; 20 credit hours of electives or independent research; and 24 credit hours of dissertation research. The course work is organized as follows:
If the undergraduate record does not include basic biochemistry, the student will be required to take a basic biochemistry course prior to the BINF 701 Biochemical Systematics (Biochemistry). If the undergraduate record is otherwise insufficient, the student may be required to take prerequisite courses, some of which may not be applicable to the 48-hour course total for the bioinformatics Ph.D. 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. By the end of the semester when course work is completed, the student must form a doctoral committee, which will supervise the student's candidacy examination. The examination includes written and oral components. Upon passing the candidacy examination and submitting an acceptable dissertation proposal, the student is advanced to doctoral candidacy. Climate Dynamics, Ph.D.The mission of the Ph.D. in Climate Dynamics degree program is to train the next generation of world leaders in the science of climate dynamics. While there is no unambiguous definition of "climate," climate dynamics is generally considered to encompass processes that determine the behavior of the atmosphere, land, and oceans averaged over timescales of weeks to centuries and millenia. Understanding climate variability and predictability poses difficult mathematical, computational, and observational questions that have generated increasing intellectual excitement in recent years. Because atmospheric behavior is strongly coupled to the oceans and land surface, physical oceanography and land surface physics can also be considered part of the science of climate dynamics. Understanding climate variability has important ramifications for society, from planning for next year's electrical demand and forecasting agricultural production, to answering complex questions involving long-term global change. While it is thought to be theoretically impossible to predict day-to-day weather more than a few weeks in advance, recent progress in predicting El Niño supports the idea that seasonal averages of temperature, rainfall, etc., may be at least partly predictable months or even years in advance. The climate dynamics faculty of SCS is varied and consists of a blend of expertise in dynamics, statistics, and computational methods, while covering the traditional areas of atmospheric dynamics, physical and dynamical oceanography, and land surface physics. Faculty research focuses on the areas of climate prediction and predictability; climate variability; coupled ocean-atmosphere-land dynamics; and dynamical systems and retrospective analysis. Recent research topics include:
External research collaborations exist with federal agencies, private corporations, and other universities, exemplifying the commitment of SCS and George Mason University to the development of effective regional and national collaborations. The climate dynamics faculty is heavily involved with national and international climate science efforts, providing students with the opportunity for participation in such research efforts. Degree RequirementsThe degree will be awarded upon completion of the required course work and approval of a Ph.D. thesis that makes an original and significant contribution to the field of climate dynamics. The curriculum is divided into four logical areas: 12 credit hours of fundamental climate science courses; 9 credit hours of core computational methods; 3 credit hours of seminar; a minimum of 24 credit hours of electives; and a minimum of 24 credit hours of dissertation research. The course work is organized as follows:
Close to the time that course work is completed, each student must form a dissertation committee. This committee prepares and administers a qualifying examination for the student. Following successful completion of the qualifying examination, the student presents a written dissertation proposal to the committee. The student may enroll in CSI 998 Doctoral Dissertation Proposal to complete this effort. After approval of the dissertation proposal, the student is formally advanced to candidacy for the Ph.D. degree, and produces the dissertation. Computational Science, M.S.The interdisciplinary master's program in computational science addresses the growing national and regional demand for trained computational scientists. The proposed degree combines a solid foundation in information technology skills with computational courses in a variety of scientific areas. All courses are offered in the late afternoon or early evening to accommodate students with full-time employment outside the university. The degree is centered on a strong computational component, which comprises 22 hours of course work. The remaining 9 hours represent the scientific component, and centers on specific scientific areas such as mathematics, physics, chemistry, biology, statistics, etc. This provides students with a flexible set of options that can be used to create their own customized curriculum under the guidance of a faculty advisor. Students are encouraged to undertake an optional master's thesis or research project that allows them to gain useful experience in the development of simulations and other aspects of computational science. Degree RequirementsCandidates must successfully complete 31 credit hours as follows:
Bioinformatics, M.S.The M.S. in Bioinformatics degree addresses the growing national and regional demand for trained computational biologists. The degree combines a solid foundation in biotechnology with computational skills required for bioinformatics. The flexibility of the degree structure permits students to custom-design their curriculum under an advisor's guidance, making the M.S. in Bioinformatics especially relevant for students employed in today's diverse biotechnology workplace. Students completing the program are qualified to pursue careers that require knowledge of current bioinformatics methods and the ability to develop new bioinformatics software. Courses are generally offered in the late afternoon or early evening to accommodate students with full-time employment outside the university. Persons employed at area biotechnology organizations may take up to 6 credits (out of 31) for bioinformatics work done on the job under the guidance of a faculty member. This work-related project may be applied either as a 3-credit research project or as a 6-credit master's thesis. Degree RequirementsCandidates must successfully complete 31 credit hours as follows:
Research component: 3 credit hours of BINF 798 Research Project or 6 credit hours of BINF 799 Master's Thesis; exercise of the thesis option results in a corresponding reduction in the electives requirement from 12 credit hours to 9 credit hours. Earth Systems Science, M.S.The interdisciplinary master's program in Earth systems science (ESS) is offered jointly by SCS and the College of Arts and Sciences (Department of Environmental Science and Policy; Department of Geography). This degree program addresses the growing national and regional demand for trained professionals in Earth systems science and applications. The ESS M.S. degree emphasizes a research-oriented global systems approach to the study of the atmosphere, hydrosphere and lithosphere, including their interrelationships and their interactions with the biosphere. Emphasis is on the obser vation and quantitative analysis of Earth systems. Students completing the program are qualified to pursue careers that require knowledge of the basics of Earth systems science and the requisite tools. Students are encouraged to undertake either an optional master's thesis for more in-depth studies or a research project. In the latter case, students will have to pass a qualifying exam. Degree RequirementsCandidates must successfully complete 30 credit hours as follows:
Certificate in Computational Techniques and ApplicationsSCS offers a graduate certificate program in computational techniques and applications (CTA), which focuses on mastering a variety of basic computational skills. The CTA certificate is independent of the doctoral and master's programs and is designed primarily for professionals in technical fields who may wish to upgrade their computer expertise. This program is also available as an option for prospective or currently enrolled doctoral or master's students. The certificate program is composed of 15 credits of course work designed to provide an accelerated introduction to concepts in modern computation. Topics include operating systems, environments, languages, graphics, databases, and applications. Nondegree status is available for professionals who are interested in taking a limited number of courses. FacilitiesComputation is recognized as a central feature of the instructional and research programs of SCS. The school, therefore, continues to establish world-class computational facilities. In addition, high-speed Internet connections permit interactive distance learning and access to remote databases. The Fairfax Campus offers instruction in all areas of the SCS curriculum, and provides state-of-the-art computational laboratories and electronic classrooms for research and interactive instruction. The SCS Graduate Instructional Computational Facility houses 24 Silicon Graphics workstations clustered with a 100 GB RAIDS system. These machines are configured with state-of-the-art software for symbolic manipulation, modeling, simulation, data analysis, database management, and data visualization. Other advanced computing platforms within SCS include a high-performance parallel PC cluster with 134 processors, an SGI Origin 2000 workstation with 16 processors, an SGI Origin 200, an SGI Onyx with infinite reality graphics engine, and an Octane visualization workstation. SCS students are issued computer accounts and access to the SCS instructional facilities. Other computing platforms are available for research by graduate students. SCS facilities on the Prince William Campus are partially shared with the American Type Culture Collection, the world's largest collection of living biological cultures. Facilities include molecular biology and biochemistry labs, computer labs, cold rooms, and instrument rooms, as well as faculty offices. Available computer facilities include more than 60 SGI workstations, including a four-processor Onyx, 18 Octanes, and more than 40 O2s. An SGI Origin 200 provides more than 65 GB of high-availability RAID disk storage. Other computational resources include SUN SparcStations, Macs, and PCs. All computers are connected via a high-speed (100 MB/sec) Ethernet LAN. Teaching facilities include three computer classrooms equipped with SGI workstations configured with advanced bioinformatics, visualization, and data-mining software. Three wet labs for teaching and training are supported by adjacent computer labs, lecture rooms, prep labs, and equipment labs, including three ABI 377 and two ABI 310 automated DNA analyzers. |