Master's Degree In Computational Science and Engineering

Mission

Computational Science and Engineering (CSE) is an interdisciplinary graduate program (granting M. S. and Ph. D. degrees) designed for students who seek to use advanced computational methods to solve large problems in diverse fields ranging from the basic sciences (Physics, chemistry, mathematics, etc.) to sociology, biology, engineering, and economics. 

The mission of Computational Science and Engineering is to graduate professionals who (a) have expertise in developing novel computational methodologies and products,  and/or (b) have extended their expertise in specific disciplines (in science, technology, engineering, and socioeconomics) with computational tools.

Objectives

The Computational Science and Engineering programs have been designed with the following objectives:

  • To lead graduate students to a mastery of high-performance computer programming tools as methods, as well as the acquisition, processing and analysis of large datasets.
  • To educate and train students in computational modeling, simulation and visualization.
  • To educate and train students in obtaining computational solutions to problems of high dimensions or involving large datasets.
  • To assist students in relating and applying the acquired computational science and engineering knowledge and skills to specific application fields of engineering, science, technology and business with expertise in the associated domain fields and their computational aspects.
  • To teach students to develop novel and robust computational methods and tools to solve scientific, engineering, technology, and business problems.
  • To produce highly versatile computational scientists, engineers, technologists, or business executives with a good understanding of the connections among various disciplines, capable of interacting and collaborating effectively with scientists, engineers, and professionals in other fields.
  • To increase the number of graduate professionals available to work in computational science and engineering.
  • To increase the diversity of graduate professionals, especially underrepresented minority and African Americans available to work in the computational science and engineering field.
  • To assist the State of North Carolina and the Nation to increase the pool of graduates with training and experience in computational science and engineering, interdisciplinary applications, and research.

Admission Requirements for the M.S. Degree

Background:  Applicants to the M. S.in CSE degree must possess an approved Bachelor of Science or Bachelor of Engineering degree. Approved degrees include:

  • A Bachelor of Science or of Engineering in Engineering, Physics, Computer Science, or Mathematics from an accredited program for Applicants into the Computational Methods Track; or
  • A Bachelor of Science degree in Engineering, Physics, Computer Science, Mathematics, Chemistry, Biology, Business, Agricultural Sciences, or Technology for Applicants in the Computational Applications Track.

General prerequisites:  All Applicants are expected to possess knowledge in (a) College chemistry and physics and (b) College mathematics. Applicants to the Computational Methods Track are also required to possess knowledge of (c) Calculus through differential equations, and (d) elementary numerical analysis or one semester of linear algebra.  Programming skills and working knowledge of at least one high-level programming language such as FORTRAN, C++, or an interpreted language like Java, MATLAB, or Mathematica are required for the Computational Methods Track, and are recommended for the Computational Applications Track students on the student’s area of interest.

Graduate School requirements: Applicants to the M. S. Program must comply with the requirements for admission as specified by the School of Graduate Studies for all M. S. programs.  In particular, they must comply with:

  1. The TOEFL and GRE examination requirements;
  2. Requirements regarding official transcripts for all college-level academic work;
  3. Requirements regarding Letters of Recommendation; and
  4. Completing an Application and paying all application fees

Other Requirements:  In addition to the requirements of the School of Graduate Studies,

  1. The Applicant shall provide a “Statement of Purpose” in the context of pursuing the M. S. degree in Computational Science and Engineering.
  2. An applicant requesting financial aid is strongly encouraged to provide a resume.

Computational Science and Engineering Tracks

 All students in the M.S. program will complete a set of four core courses. In addition, based on their domain background and undergraduate discipline, the following tracks are identified to assist with their domain course selection, guidance, and advice.

Computational Methods Track

This track is designed primarily for students with undergraduate degrees in engineering, chemistry, physics, mathematics, and computer science who will be trained to develop problem-solving methodologies and computational for solving challenging problems. Students in this track typically possess significant prior training in fields such as mathematics, numerical analysis, and high-level programming languages.

Students with undergraduate degrees in other science and technology fields may also be admitted if they meet the admission and course requirements, including prerequisites of the domain department.

Research in this track includes but is  not  limited to computational quantum chemistry, computational nuclear and high-energy physics, computational solid or fluid dynamics, computational material science, bioengineering, computational geometry, computational nonlinear dynamics, computational statistics, engineering design and automation, applied and environmental geophysics, computational seismology, nonlinear computational mechanics and dynamics, super fast algorithms for numerical and algebraic computation, and distributed and high-performance computing.

Computational Applications Track

This track is designed primarily for students with undergraduate degrees in chemistry, biology, psychology, business, finance and economics, technology and engineering, and agricultural sciences who will be trained to apply or extend computational tools and methods, as well as data acquisition, processing and visualization techniques, to study computationally intensive problems in their disciplines.  This track often includes domain courses requiring lesser training in mathematics and computational technology. Based on their undergraduate field, the students in this track will be typically required to take additional mathematics- and programming-focused courses.

PROGRAM OPTIONS AND DEGREE REQUIREMENTS

The M.S. program in computational science and engineering requires 34 credit hours at the graduate level beyond the undergraduate degree distributed as follows:

       Thesis Option:

  •         27 credit hours for course work at the graduate level,
  •         1 credit hour for seminars, and
  •         6 credit hours for thesis research. 

       Project Option:

  •         30 credit hours for course work at the graduate level,
  •         1 credit hour for seminars, and
  •         3 credit hours for graduate masters project.  

Core Course Requirements

This track is designed primarily for students with undergraduate degrees in chemistry, biology, psychology, business, finance and economics, technology and engineering, and agricultural sciences who will be trained to apply or extend computational tools and methods, as well as data acquisition, processing and visualization techniques, to study computationally intensive problems in their disciplines.  This track often includes domain courses requiring lesser training in mathematics and computational technology. Based on their undergraduate field, the students in this track will be typically required to take additional mathematics- and programming-focused courses.

CSE 701

Applied Probability and Statistics

CSE 702

Comprehensive Numerical Analysis

CSE 703

Data Structures, Software Principles and Programming in Scalable Parallel Computing

CSE 704

Computational Modeling and Visualization

CSE 801

Advanced Statistics and Experimental Design

CSE 802

Advanced Numerical Analysis

CSE 803

Advanced High Performance and Scalable Computing

CSE 804

Advanced Scientific Visualization

CSE 805

Visual Analytics and Data Mining   

CSE 806

Computational System Theory

Points of Pride