Computer Science, PHD
Chairperson: Dennis Brylow, Ph.D.
Program Director: Praveen Madiraju, Ph.D.
Computer Science website
Degree Offered
Doctor of Philosophy
Program Description
The computer science graduate program prepares students for careers in research in industry, research laboratories and institutions of higher education. The program allows students to tailor course work based on their interests and strengths and places particular emphasis on students contributing to applied research in computer science.
Doctoral students acquire a master of science degree in computer science as they progress toward their doctoral degree.
CAREER SKILLS REQUIREMENT FOR PH.D. STUDENTS
Marquette University is committed to preparing our students to become exemplary leaders in their chosen academic and professional fields by preparing them for careers in which they find purpose and value by engaging in Ignatian pedagogical reflection and practice. The purpose of the career skills requirement is to ensure all doctoral students have the opportunity to reflect on their desired career and to acquire essential career-related skills needed for them to pursue their chosen path.
Students enrolled in Ph.D. programs in Fall 2024 and beyond at Marquette must complete three career skills requirements. Requirements are satisfied by one or more of approved courses, workshops, or practical experiences in each category, as approved by the Graduate School. Completion of each skill will be noted on the student’s transcript.
CAREER DISCERNMENT
Students will be able to identify and prepare for career pathways that are consistent with their values.
Objectives:
- Understand realities of academic job market for your discipline, creating space for career imagination and understand potential career paths.
- Exploration of, and defining student’s own identity/experiences/values/strengths/gifts and how the career pathway fits with those values.
- Students will learn to identify and attain the skills and experiences necessary to obtain the career pathway they desire.
Code | Title | Hours |
---|---|---|
Choose 1: | ||
GRAD 8097 | Career Discernment/Career Diversity Skills (Career Development Bootcamp) | 0 |
GRAD 8097 | Career Discernment/Career Diversity Skills (Seminar Series) | 0 |
GRAD 8097 | Career Discernment/Career Diversity Skills (Ph.D. Pathways) | 0 |
COMMUNICATION
Students will be able to communicate their ideas and scholarship effectively to audiences beyond those in their discipline.
Objectives:
- Demonstrate the ability to communicate (e.g., research, expertise, experiences) effectively and ethically with disciplinary, cross-disciplinary, and nonacademic audiences.
- Demonstrate the ability to communicate effectively and ethically within various contexts, formats, and media.
- Demonstrate the ability to effectively deliver a presentation and facilitate discussion.
Code | Title | Hours |
---|---|---|
Choose 1: | ||
GRAD 8098 | Communication Skills (Seminar Series) | 0 |
GRAD 8098 | Communication Skills (Three Minute Thesis) | 0 |
GRAD 8961 | Science Storytelling | 1 |
UNDERSTANDING DIVERSITY, EQUITY AND INCLUSION
Students will understand the importance of diversity, equity and inclusion and how issues of DEI are relevant to their career pathways.
Objectives:
- Be aware of and able to identify how explicit and implicit bias impacts work life and understand possible strategies to address this bias.
- Be able to articulate the value of universal design principles and ethical application to area of study.
- Be able to work and interact effectively with persons from diverse backgrounds with varied values, ideas, and opinions.
Code | Title | Hours |
---|---|---|
GRAD 8099 | Diversity, Equity and Inclusion Skills | 0 |
Computer Science Doctorate
A doctoral student in computer science must first complete a plan of study on an approved Doctoral Program Planning Form, designed to see the student through completion of the qualifying examination. This plan of study should be prepared in cooperation with an adviser and approved by the Graduate Committee of the Department of Computer Science.
All newly admitted doctoral students who begin the program without an earned master’s degree in an acceptable field will automatically be dually enrolled in the computer science master of science program. Students will earn the computer science master's degree while completing the computer science doctoral degree requirements, provided they satisfy the master's program requirements.
The total 57-credit program includes a minimum of 45 credit hours of approved course work beyond the bachelor's degree in computer science or related field plus 12 dissertation credits. Students must complete:
- 2 credit hours of COSC 6090 Research Methods/Professional Development, completed by the second year. COSC 6090 is a 1 credit hour class and must be taken twice to earn two (2) credit hours.
- Core Course Work (15 credit hours)
- COSC 6975 Curriculum Integrated Practicum in Computer Science (0 credit hours). Students are required to enroll once in COSC 6975 – zero (0) credit hour course and may enroll up to a maximum of two times during their degree program.
- Electives (28 credit hours).
- Elective course work must be chosen based on mutual agreement of the student and their adviser’s mutual research interests. Each student is advised to take such courses as are properly related to academic background and research interests.
- A maximum of sixteen (16) credit hours of COSC 6960 Seminar in Computer Science or Independent study ( COSC 6995 / COSC 8995) are allowed as electives. Only nine (9) of the sixteen (16) credit hours may be taken as independent study.
- A maximum of twelve (12) credit hours may be taken at the 5000 level.
- A maximum of six (6) credit hours may be taken outside the department.
- Twelve (12) credit hours of COSC 8999 Doctoral Dissertation. Students may start registering for dissertation credit hours around the time of their qualifying exam, but should not complete all 12 credit hours before passing the qualifying exam.
Advancement to candidacy for the doctoral degree is considered following successful completion of the lecture course work specified in the Doctoral Program Planning Form and after passing the qualifying examination (written and oral). Following advancement to candidacy, students must submit a Dissertation Research Plan that is approved by their advisory committee. Their proposal (written and oral) and dissertation (written and oral) must be approved.
The residency requirement for COSC doctoral students is met when the student has completed either (i) three consecutive semesters with a minimum of three credits of course work each semester or (ii) three consecutive semesters with a minimum of one credit of COSC 6960 Seminar in Computer Science or COSC 6090 Research Methods/Professional Development each semester. Summer can be, but is not required to be, included to meet the residency requirement.
Code | Title | Hours |
---|---|---|
COSC 6090 | Research Methods/Professional Development (1 credit, taken at least twice) | 2 |
Core Course Work | ||
Theory - choose one of the following: | 3 | |
Advanced Algorithms | ||
Advanced Machine Learning | ||
Software Systems - choose two of the following: | 6 | |
Distributed and Cloud Computing | ||
Advanced Operating Systems | ||
Advanced Computer Security | ||
Big Data Systems | ||
Applications - choose two of the following: | 6 | |
Elements of Software Development | ||
Data Security and Privacy | ||
Data Ethics | ||
Approved Elective courses (no more than 12 credits taken at the 5000 level) 1 | 28 | |
Real-Time and Embedded Systems | ||
Network Design and Security | ||
Software and System Security | ||
Compiler Construction | ||
Visual Analytics | ||
Fundamentals of Artificial Intelligence | ||
Data Mining | ||
Principles of Database Systems | ||
Component-Based Software Construction | ||
Elements of Software Development | ||
Software Quality Assurance | ||
Distributed and Cloud Computing | ||
Research Methods/Professional Development | ||
Advanced Algorithms | ||
Advanced Operating Systems | ||
Advanced Computer Security | ||
Advanced Machine Learning | ||
Component Architecture | ||
Mobile Health (mHealth) | ||
Distributed Computing | ||
Mobile Computing | ||
Enterprise Architecture | ||
Web Technologies | ||
Big Data Systems | ||
Data Intelligence | ||
Data Analytics | ||
Concepts of Data Warehousing | ||
Introduction to Cybersecurity | ||
Principles of Service Management and System Administration | ||
Data at Scale | ||
Data Security and Privacy | ||
Data Ethics | ||
Topics in Computer Science | ||
Seminar in Computer Science (may be taken more than once) | ||
Independent Study in Computer Science (may be taken more than once) | ||
Independent Study in Computer Science (may be taken more than once) | ||
Time Series Analysis | ||
Statistical Machine Vision | ||
Regression Analysis | ||
Bayesian Statistics | ||
Digital Processing of Speech Signals | ||
Chaos and Nonlinear Signal Processing | ||
Pattern Recognition | ||
Neural Networks and Neural Computing | ||
COSC 6975 | Curriculum Integrated Practicum in Computer Science (required to enroll once, but may enroll up to two times) | 0 |
COSC 8999 | Doctoral Dissertation | 12 |
Total Credit Hours: | 57 |
1 | Students must work closely with advisers to create individualized plans of study, depending on the mutually agreed upon focus area. Not all electives in this list are available to all students. |
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