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  • Computer Science (Ph.D.)
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Ph.D. in Computer Science

Gain vital expertise to lead and innovate with the help of invaluable "practice experience" in a fast-paced, real-world environment.

Through critical and logical thinking, you’ll gain the essential knowledge and experience needed to become highly proficient in the use of today’s leading computing platforms and techniques.

Program type:
Doctoral Degree
Format:
On Campus or Online
Est. time to complete:
4-5 years
Credit hours:
90 (approved bachelor's degree); 60 (approved master's degree)
  • Requirements
  • Tuition & Fees
  • How to Apply
  • Why UND Online?
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Why earn a Ph.D. in computer science?

Application Deadlines
Fall:
Aug. 1
Spring:
Dec. 1

Scientists and engineers in every industry rely on high-performance technology and large data sets, requiring experts that can help harness the latest sophisticated computing power to solve real-world problems.

With this graduate program, you'll:

  • Get essential "practice experience" to help solve real-world problems and challenges through computational technology
  • Develop the knowledge and skills that will prepare you to lead or support research in any technical career that relies on computer science.
  • Develop your logic and critical-thinking skills to help solve today's most pressing scientific and engineering challenges.
  • Choose from computation clusters focused on specialized computing system or methods, and application clusters for exposure to specific scientific disciplines.
  • Work with practitioners in a variety of disciplines served by computer science.

On-Campus or Online Ph.D. in Computer Science

  • Benefit from strong departmental proficiencies in artificial intelligence, compiler design, database, networks, operating systems, graphics, simulation, software engineering, and theoretical computer science.

  • Gain the expertise need to follow a career path in many dynamic branches of computer science such as bioinformatics, atmospheric science, software design, and more.

  • Advance your technology skills with a curriculum that encourages a formal, abstract, theoretical and practical approach to the study of computer science.

  • Gain access to on-campus computer power: two computer labs, a set of diverse servers and a high-performance computing (HPC) system. The supercomputer at UND runs on the HPE Apollo 6500 Gen10 system, purpose-built for HPC and a leading platform for deep learning. 

  • UND is a leader in big data expertise. We are the lead institution in a multi-university project for digital agriculture, funded by the National Science Foundation. And we  co-lead another NSF project to determine industry and academic computational needs in the Midwest.

  • Study at a Carnegie Doctoral Research Institution ranked #151 by the NSF. Students are an integral part of UND research.

What can I do with a Ph.D. in computer science?

21%

Job growth outlook for Computer and Information Research Scientists by 2031

U.S. Bureau of Labor Statistics

131K

Average median salary of Computer and Information Research Scientists

U.S. Bureau of Labor Statistics

Graduates of this program often go on to successful careers as software engineers and developers, computational scientists, data science engineers, research scientists at technology companies and universities.

Because technology systems are so essential today in many areas of science, technology and research, UND graduates can expect career opportunities across a range of industries. A small sampling of top industries needing scientific computing skills include:

  • High tech (hardware)
  • Software engineering
  • Scientific and medical research (private and university-level)
  • Engineering and science
  • Renewable energy
  • Communications
  • Aerospace

Ph.D. in Computer Science Courses

CSCI 515. Data Engineering and Management. 3 Credits.

This course studies theoretical and applied research issues related to data engineering, management, and science. Topics will reflect state-of-the-art and state-of-the-practice activities in the field. The course focuses on well-defined theoretical results and empirical studies that have potential impact on data acquisition, analysis, indexing, management, mining, retrieval, and storage. Prerequisite: CSCI 513. S, even years.

CSCI 543. Machine Learning. 3 Credits.

An introductory course in machine learning for data science. Topics include the learning algorithms of a Bayesian network, neural network, parametric/non-parametric methods, kernel machine, support-vector machine, etc. for regression, classification, clustering, dimensionality reduction, etc. Prerequisite: CSCI 365 or CSCI 384. F, odd years.

CSCI 567. Secure Software Engineering. 3 Credits.

This course covers software engineering principles and techniques used in the development life-cycle of cyber secure systems. Topics covered include, the characteristics of secure software, the role of security in the development life-cycle, designing secure software, and best-practices in secure programming and testing. Study includes review of industrial standards for secure software system engineering. Prerequisites: EE 601, EE 602, and admission to the MS Cyber Security Program. SS.

CSCI 554. Applications in AI/Computational Intelligence. 3 Credits.

A continuous study of the computational paradigms of Soft Computing in the field of Computational Intelligence. The topics include the applications of the various soft computing techniques in Computational Intelligence as well as more evolutionary algorithms in Swarm Intelligence. Prerequisite: CSCI 544. F, even years.

CSCI 555. Computer Networks. 3 Credits.

A study of new and developing network architectures and communication protocols. Broadband technologies will be considered including BISDN, ATM networks, and other high-speed networks. Prerequisite: CSCI 327.

CSCI 557. Computer Forensics. 3 Credits.

An overview of the techniques to detect and assess the level of penetration of a security breach. Topics include forensic science in the cyber domain, laws and ethics of forensic activities, digital evidence, methods of forensic investigation, and forensic procedures in a variety of operating systems and network configurations. Prerequisite: EE 602, or approval of the department, and admission to the MS program in Cyber Security. S.

Leaders in Computer Science

As a leader of Big Data, UND's goal is to make things more efficient, more effective and safer for North Dakotans.

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Explore More Options

Check out the faculty you'll work with at UND or discover additional education opportunities.

  • School of Electrical Engineering & Computer Science
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Department Contact
Ryan Adams
Graduate Director
P 701.777.5644
ryan.s.adams@UND.edu
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