Computer Science PhD Program
Program Mission:
The PhD Program in Computer Science at KAUST cultivates world-class researchers capable of advancing fundamental and applied knowledge at the highest levels of scientific rigor. Through deep engagement with KAUST’s cutting-edge laboratories, interdisciplinary collaborations, and global research community, doctoral students are empowered to pursue original discovery, develop transformative technologies, and generate lasting impact for science, industry, and society. The program prepares graduates to become leaders who drive innovation and contribute to Saudi Arabia’s ambitions for global excellence in research and technological advancement.
Program Goals:
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Provide students with a rigorous and comprehensive doctoral education that deepens expertise in advanced computer science theory, methods, and research practices.
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Develop the ability to conduct original, high-impact research by immersing students in KAUST’s cutting-edge laboratories, interdisciplinary collaborations, and global research networks.
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Prepare graduates for leadership roles in both academia and industry by cultivating advanced analytical skills, technological fluency, and the capacity to drive innovation in emerging and strategically important fields.
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Equip doctoral researchers to generate meaningful scientific and societal impact by creating new knowledge, developing transformative technologies, and contributing to Saudi Arabia’s aspirations for global excellence in research and technological advancement.
Program Learning Outcomes (PLOs)
Knowledge and Understanding
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K1 Deep and specialized knowledge of the fundamental theories, principles, and concepts underpinning Computer Science, including algorithm design and analysis, data structures, computational complexity, programming languages, computer architecture, operating systems, networking, databases, and software engineering.
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K2 Expertise in established and specialized research methods in computer science, including algorithmic analysis, formal verification, simulation and modeling, empirical experimentation, statistical and data-driven approaches, and the use of advanced computational tools to support original inquiry.
Skills
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S1 Solve complex problems by designing efficient algorithms, optimizing system performance, and integrating multiple computing paradigms to address advanced technical and interdisciplinary challenges.
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S2 Conduct advanced research and professional projects using specialized methodologies, including formal methods, simulation and modeling, experimental design, and data-driven inquiry.
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S3 Use advanced tools, techniques, and processes—including programming languages, software development environments, cloud platforms, and high-performance computing systems—to carry out complex computational tasks.
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S4 Carry out advanced procedures such as system integration, security testing, performance evaluation, and deployment of applications in specialized domains.
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S5 Communicate complex technical information, research findings, and innovative solutions effectively through reports, presentations, and visualizations tailored to both expert and non-specialist audiences.
Values, Autonomy, and Responsibility
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V1 Demonstrate integrity, ethical reasoning, and professional responsibility in all aspects of Computer Science practice, including data management, algorithmic design, software development, and research.
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V2 Independently initiate and manage professional learning and development, plan research agendas, and contribute to strategic decision-making in academic and industry contexts.
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V3 Collaborate effectively in interdisciplinary teams, taking leadership roles in research, development, and professional projects while assuming responsibility for outcomes and quality.
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V4 Contribute to societal well-being by applying computer science knowledge and skills to address global challenges, promote sustainability, and improve the quality of life through innovative and ethical technological solutions.
PhD Course Requirements
Students entering the PhD Program must complete the requirements below:
- 300-level courses* (6 credits)
- Graduate Seminar (non-credit)
- Winter Enrichment Program (non-credit)
The Academic Advisor may request the completion of additional courses. Courses taken while pursuing the KAUST MS degree cannot be counted towards the PhD course requirements. Courses must be technical courses and cannot be substituted with Research, Internship, or Broadening Courses to fulfill degree requirements.
*One course must be a CS course (excluding CS 394).
Graduate Seminar (non-credit)
Students must register for CS 398 and receive a Satisfactory grade for two Semesters during their PhD, even if they attend them during their MS.
Winter Enrichment Program (non-credit)
All students must complete the Winter Enrichment Program (
WE 100) for credit at least once during their studies at KAUST. Students who have previously completed WEP will be exempt from this requirement in their future studies.
PhD Candidacy
In addition to the coursework requirements, students must successfully complete the required PhD candidacy milestones to progress toward PhD candidate status. These milestones are as follows:
- A subject-based qualifier
- PhD Proposal Defense
Once students have advanced to candidacy, students are designated as PhD or Doctoral Candidates.
Qualifying Exam
Students must pass the qualifier within three Semesters and one Summer Session of commencing the PhD program. The CS qualifier is course-based. Students must pass three courses to pass the qualifier using the following rules:
- One of the courses must have a grade of A- or A; the other two must have a grade of B+ or better.
- All three courses must be selected from eligible qualifier courses. The list of eligible qualifier courses is available on the CS website. The list sorts all eligible qualifier courses into several research areas. The qualifier courses must be from three different research areas.
- The three courses must be taught by three different Faculty.
Additional details about the procedure of the qualifier:
- The KAUST PhD program stipulates that students must take at least two 300-level courses during the PhD candidacy. These two courses may be used as qualifier courses.
- PhD students can use courses they completed before starting their PhD as qualifier courses, e.g., courses taken while completing an MS at KAUST.
- No waiver will be given for any courses taken outside of KAUST.
- The list of eligible courses, the research areas, and the way the courses are sorted into research areas can change over time. Students should choose courses and areas according to a single version of the course list: either the version of the eligible course list that was current at the time of the start of the PhD or an eventual updated later version.
- As soon as students pass the qualifier, they should submit a filled-out qualifier form to the GPSA including a transcript. The qualifier form is available on the CS website. Upon verification, students will receive confirmation that they have passed the qualifier.
Dissertation
For more details on the Qualifying Exam results, Dissertation Proposal Defense and committee formation, Proposal Defense results, Petition to Defend the Dissertation and committee formation, Dissertation Defense results, Dissertation document, and Dissertation archiving, please refer to the Policy page.