Program Details

Computer Science (Ph.D.) | Graduate

From the use of AI technology to drive advancements in healthcare to the use of blockchain technology to accelerate business growth and predict disease outbreaks, computer science is driving economic growth and innovation. Our doctoral graduates are prepared for leading careers in academia, research, industry, and government.

• Degree Classification: Graduate
• Related Degrees: Ph.D.

Application for Admission

• Online EngineeringCAS application
• Statement of purpose/ Statement of academic interest (500-1,000 words) (Guidance here)
• GRE scores not required
• Official transcripts sent to EngineeringCAS
• 3 letters of recommendation
• Bachelor's degree from an accredited college or university or the international equivalent
• Resume or Curriculum Vitae
• Autobiographical statement (500-750 words) (Guidance here)

GRE Required?

• No

GRE Preferred Minimums    

• GRE Verbal Reasoning: N/A
• GRE Quantitative Reasoning: N/A
• GRE Analytical Writing: N/A

GPA Required Minimums    

• Overall GPA minimum: 3.0
• Undergrad GPA minimum: 3.0

Prerequisite Courses (Recommended)

The following course prerequisites are recommended. No expiration date for recommended prerequisites.

• Programming (6 semester credit hrs of programming coursework or working knowledge of at least 2 programming languages including C, C++, or Java)
• Data Structures (3 semester credit hrs or a course that exposes students to basic data structures of linked lists, stacks, queues, and trees. Applicants should have extensive experience in writing programs that implement algorithms for manipulating these data structures)
• Machine Organization (3 semester credit hrs or a course involving machine organization.This requirement can be fulfilled by a course in operating systems, assembly language programming, computer organization, computer architecture, or a similar course)
• Operating Systems (3 semester credit hrs or a course in operating systems)
• Algorithms (3 semester credit hrs or a course in computer science that requires data structures as a prerequisite. This requirement can be fulfilled by a course in algorithms, algorithm analysis, numerical analysis, or a similar course algorithm analysis, numerical analysis, or a similar course)
• Probability or Statistics (3 semester credit hrs of probability and statistics or an equivalent course)
• Calculus (6 semester credit hrs of a calculus course)
• Differential Equations, Linear or Abstract Algebra, or Discrete Math (3 semester credit hrs of upper-level courses in differential equations, linear algebra, abstract algebra, or discrete mathematics. The course should have calculus as a prerequisite)

Reference Requirements    

Evaluator type accepted:

• Professor (Required)
• Supervisor/Manager
• Coworker

Evaluator type not accepted:

• Friend
• Family Member
• Clergy
• Other