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Online PhD Computer Science Admission Colleges in World, Syllabus, Eligibility, Entrance Exam, Job Scope, Salary

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Online PhD in Computer Science


Gain vital expertise to lead and innovate with the help of the 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


  • On-Campus or Online

Est. time to complete:

  • 3 years

Credit hours:

  • 90 (approved bachelor’s degree); 60 (approved master’s degree) 

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 the 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 the specialized computing system or methods, and application clusters for the exposure to specific scientific disciplines.

Work with practitioners in the variety of disciplines served by computer science. 

On-Campus or Online PhD in Computer Science

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

Gain the expertise need to follow the 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 the 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-led another NSF project to determine industry and academics computational needs in the Midwest. 

A study at the Carnegie Doctoral Research Institution ranked #151 by the NSF. Candidates are an integral part of UND research. 

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

Because technology systems are so essential today in many areas of sciences, 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 (privates and university-level)

·         Engineering and science

·         Renewable energy

·         Communication

·         Aerospace 


  • Data Engineering and Managements
  • Machine Learning
  • Secure Software Engineering
  • Applications in AI or Computational Intelligence
  • Computer Networks
  • Computer Forensic 

There may be a few foundational classes that all computer science doctoral candidates are required to take. In addition, you may need to ensure that your course schedule includes at least one class from each required category; for example, you may need a theory class, a programming class, and an applications class. 

Artificial Intelligence – your time in this class can help bring you up to speed on some of the latest advancements in artificial intelligence and give you an idea of the direction that this technology may be heading. You’ll likely discuss search algorithms and the probabilistic models.

Databases – this course explores advanced topics in creating and using databases. Data analytics will likely be an important component of your studies, and you’ll probably discuss query optimizations and warehouse modeling.

Graduate Algorithms – this course can help equip you with skills and tools for advanced data collection and analysis. The topics may include hash tables, linear programming, max-flow algorithms, and dynamic programming.

Programming Languages – your earlier academic programs probably introduced you to the basics of using programming languages, and this doctoral course is designed to build on your object-oriented and functional programming skills. You’ll likely talk about applying algorithms and running optimizations.

Project Management for Software Design – creating a new program or operating system can involve coordinating numerous people over a long span of time. This class covers how to provide organized leadership for the process and ensure that all the involved parties stay on the same page.

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