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Computational Science and Engineering (CSE) option 

Computational Science and Engineering (CSE) is now an integral part of scientific research and engineering design in which large-scale, dynamic simulation and high-performance computing play a central role.  Students electing the CSE option become proficient in advanced computing methods as well as in one or more applied disciplines in science, engineering, mathematics or medicine.  The CSE option fosters and coordinates interdisciplinary, computationally-based research and education and prepares students to solve complex technological problems.  Graduates are highly sought by research and development focused industries, institutions and government laboratories.

Core Courses Requirements

The core curriculum for the CSE option includes 9 hours of foundational courses in Mathematical/Computational Methods and High Performance Scientific Computing plus enrollment in EAS/CSE seminars.  The latter courses are important to maintain cohesion within the group and to encourage exchange of ideas from a variety of perspectives.

Specialization Course Requirements

A minimum of 18 additional hours of coursework is required for post-baccalaureate students.  Course selection is based on the research and career goals of the student, and curricula will vary between students.  The coursework must include courses from at least two disciplines.  These courses are usually taken in mathematics, physics, engineering, or computer science.

Dissertation Research

This work is completed under the guidance of the students' faculty advisor. More information about faculty and research opportunities in the Scientific Computing group can be found here.

A typical curriculum plan for the CSE option is shown below.

Graduate Program Curriculum Outline

Computational Science and Engineering Option


Major Required (Core) Courses (Total # of courses required = 7)

Course Number

Course Title

Credit Hours

EAS 501

Advanced Mathematical Methods


EAS 502

Computational Methods


EAS 520

High Performance Scientific Computing


EAS 621

Scientific Computational Research Seminar


EAS 622

Scientific Computational Research Seminar


EAS 600

Dissertation Proposal Preparation


EAS 601/701

Doctoral Dissertation Research


EAS 602

Research Ethics


EAS 700

Doctoral Seminar



Subtotal # Core Credits Required



Elective Course Choices (Total courses required =6) (attach list of choices if needed)

MTH/PHY 500-600

4 x Major Electives (example list attached)


COE/DIS 500-600

2 x Graduate Electives (Minor)



Subtotal # Elective Credits Required


Curriculum Summary


Total number of courses required for the degree



Total credit hours required for degree                             



Prerequisite, Concentration or Other Requirements:

Ph.D. Qualifying Examination (QE) and Comprehensive Exam:  Each student must pass a qualifying exam and a comprehensive exam on research preparedness prior to becoming a doctoral candidate.



Major Electives for Computational Science and Engineering Option include any graduate-level course in MTH or PHY. Some examples include:


MTH 521

Numerical Methods for Ordinary Differential Equations


MTH 572

Numerical Solution of Partial Differential Equations


MTH 573

Numerical Linear Algebra


MTH 574

Numerical Optimization


PHY 521

Computational Physics


PHY 621

Advanced Mathematical Physics I


PHY 622

Advanced Mathematical Physics II




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