Student on computer

M.S. AND PH.D. IN COMPUTATIONAL SCIENCES

 

Program Description

The Department of Mathematics, Statistics and Computer Science offers both M.S. and Ph.D. study in Computational Sciences. Computational Sciences refers to the discovery, implementation, simulation, and application of models to solve scientific and engineering problems. Commonly, these efforts involve the development of new computational methodologies, computer software and/or computer systems to solve large-scale or multi-scale scientific problems that are intractable through purely theoretical methods.

Our program is designed to equip graduates with a distinctive blend of theoretical and computational skills, for employment in industry, research laboratories and institutions of higher education. While the bulk of their coursework will be undertaken in this Department, their research topics may range across the computational aspects of a broad spectrum of disciplines.

A relatively small number of programs with the same overall goals exist in this country. Most have a similar title, although their focus varies, quite naturally, according to the resources with which they are blessed. Nonetheless, each offers students the opportunity to work within an interdisciplinary setting wherein the ultimate goal is the solution of a scientific problem using state-of-the-art computational techniques.

A distinctive feature of our program is that all core aspects of a student’s program of study, constituting in general the first two years of study, are undertaken within our one interdisciplinary department. Thus the program benefits from the synergies that result while avoiding the administrative and philosophical obstacles frequently confronted by programs that cross academic divisions. In addition, students that excel in the M.S. program that decide to apply for Ph.D. program and are accepted may seamlessly enter the doctoral studies since both share our computational sciences core. Our doctoral program is designed for individuals of outstanding ability who show promise as a researcher in an interdisciplinary environment. The diverse research opportunities in our naturally interdisciplinary department are enhanced by the research programs of associated faculty on the Marquette campus in the sciences and engineering and Milwaukee area research laboratories and clinics. For a listing of department research and research laboratories, please consult the Faculty section of this web site.

Program Doctoral Graduates

 

Learning Outcomes

The Masters’ Program learning outcomes are: Apply advanced concepts related to discipline coursework to solve theoretical or applied problems. Synthesize research publications in their area. Demonstrate communication skills appropriate for presenting research to peers and interdisciplinary colleagues.

The Doctoral Program learning outcomes are: The program learning outcomes are: Modify, adapt or construct methods, techniques and software for addressing significant problems in the field of computational sciences. Conduct original research that results in a major written scholarly work in the computational sciences. Synthesize research publications in their area of specialization. Demonstrate communication skills appropriate for presenting research to peers, teaching college-level courses, or collaborating with interdisciplinary colleagues.

Prerequisites for admission

Admission to the program requires an undergraduate degree in mathematics, statistics, computer science, or a related field such as engineering or an area of science, with at least a minor (3 courses beyond a full calculus sequence) in mathematics, and proficiency in a high-level computer language. Knowing that few individuals are trained in all facets of computational sciences, we have designed our distinctive computational sciences core to provide the breath of background in mathematics, statistics and computer sciences to pursue computational sciences research. Admission to the doctoral program also requires demonstrated promise for original research.

Doctoral requirements

The total program, exclusive of dissertation (12 credits of MSCS 8999), will contain a minimum of 45 credit hours of approved course work beyond the bachelor’s degree, including the 18-credit computational sciences core (MSCS 6010-MSCS 6060), and at least 2 credits of MSCS 6090 (Research Methods/Professional Development).

Computational Sciences Core

Twelve hours of dissertation credit is also required. Approved programs of study will normally include 6 credits of courses outside the department and no more than 12 credits in 5000 number courses.

Master's requirements

Under Plan B, a student completes an approved 30 credit hour program of study and an essay. Of the 30 credit hours, 18 are the Computational Sciences Core (MSCS 6010-6060). A thesis option (Plan A) is also available.

Application deadline

January 15

Application requirements

Applicants apply online directly to the Marquette University Graduate School. For consideration, an applicant needs:

  1. To complete the online application form and submit the fee.
  2. Have official transcripts sent from all current and previous colleges/universities except Marquette.
  3. Three letters of recommendation addressing the applicant’s academic qualifications for graduate study.
  4. GRE scores (General Test only).
  5. (For international applicants only) a TOEFL score or other acceptable proof of English proficiency, English-language publications authored by the applicant, including a master’s thesis or essay, if applicable (optional, but strongly recommended).

See the Graduate School website for more detailed information on making an application to this program.

Program Doctoral Graduates

 

For more information, please contact Stephen Merrill, the Director of Graduate Studies.

 

 


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Summer 2013 Research Experience

The Department of Mathematics, Statistics and Computer Science hosted the NSF-funded Summer 2013 Research Experience (REU) for Undergraduates. This program provides U.S. undergraduates with an intensive, faculty-mentored, summer research experience in the areas of applied mathematics, high-performance computing, statistics, ubiquitous systems and mathematics education. Learn more