- With a PhD you become an expert in a topic that you’re passionate about
- In a PhD program you are able to create new knowledge and new engineering artifacts that improve the world
Why should you a consider a CS PhD at UCLA?
- US News: UCLA is the #1 public university in the country
- 2022 US News Best Computer Science Schools: UCLA CS is ranked #11
- CS rankings.org: #1 in Cryptography, #2 in Computational Biology & Bioinformatics, #3 in Artificial Intelligence, #6 in Design Automation, #7 in Machine Learning & Data Mining, # 6 in Programming Languages and Software Engineering
- UCLA CS is the birthplace of Internet with a history of computing pioneers
- UCLA has a strong and diverse campus across the board
- UCLA has a top medical school with collaboration opportunities in Health Sciences and computational medicine
- Proximity to Silicon Valley and “Silicon Beach”
UCLA PhD program has a strong faculty placement record:
In 2020-2022 hiring seasons, our PhDs and postdocs were hired as faculty at the following institutions:
- Arizona State University
- Carnegie Mellon University
- Cornell University
- Chinese Academy of Sciences
- Duke University
- Harvey Mudd College
- Institute of Computing Technology,
- New York University
- Northeastern University
- University of California, Riverside
- University of Edinburgh
- University of Hong Kong
- University of Maryland
- University of Michigan
- University of Pittsburgh
- University of Southern California
- University of Toronto
- Toyota Technological Institute at Chicago
- Penn State University
- Purdue University
- Yale University
In the past 3 years alone (2018-2022), there have been 75 Awards where half are major awards (e.g., ACM Fellow, National Academy of Engineering) involving at least 22 distinct faculty across all major fields, which is a testament to breadth of excellence in UCLA Computer Science. More comprehensive listing of faculty awards at: https://www.cs.ucla.edu/faculty-awards/
Take a look at our faculty at https://samueli.ucla.edu/search-faculty/#cs
UCLA is the first public university to host a Break Through Tech AI hub. This is part of a national program designed to teach AI to a greater diversity of students. It brings AI education to college students from underserved groups across Southern California.
UCLA has the Amazon Science Hub for Humanity and Artificial Intelligence to cross-pollinate academic and industry research.
Admission to the Ph.D. program is more selective than for the M.S. program. In general, the admissions committee does not consider Ph.D. applicants for admission into the M.S. program and vice versa. While a Ph.D. degree prepares students not only for careers in research and academia, those who apply for a Ph.D. degree typically demonstrate significant achievement in and/or potential for advancing knowledge through independent research and teaching.
Applicants who hold only a bachelor’s degree may apply to the Ph.D. program. In recent years, the majority of PhD admittees have completed only a bachelor’s degree.
The Computer Science Department has a regular Master of Science Program, which is designed to nurture the next generation of computing professionals with the required depth and breadth of computer science knowledge. The MSCS program is a part of the Computer Science department. To apply for the MSCS program, please click HERE.
Samueli School of Engineering has a one-year Master of Engineering (MEng) self-supporting, professional degree designed to develop future engineering leaders. The MENG degree addresses the needs of both students and industry, tailored to those who wish to pursue technical management positions, with both high-tech skill set and management savvy. The MEng program is not part of the Computer Science department. To apply for the MEng, go to https://www.meng.ucla.edu/admissions/
MSCS vs. MENG
The Computer Science Department offers Master’s of Computer Science (MSCS) Program, which is a 2-year program and has existed over 50 years. MEngr program is a new, one-year program. The MENG degree addresses the needs of both students and industry, tailored to those who wish to pursue technical management positions. Both MSCS and MENG programs include a capstone project with technological concentration.
Can I apply to both programs since they are housed in different departments?
No, you may only apply to one program.
What are the differences between the MEng program and the MSCS program?
The Department of Computer Science Master Program (MCSC) is a 2-year program that has existed for over 50 years. The Master of Engineering Program (MENG) is a 1-year program that is starting its 2nd year.
Number of Applications for 2022 Admissions Cycle
- MCSC (MS program in the Computer Science Department) had over 4000 applications and 150 offers were made.
- MENG (MEng program in School of Engineering) had 573 applications and 220 offers were made.
MENG Capstone topic is selected by the course instructor.
MSCS Capstone topic is student-driven in which the students decide the topic and find their capstone advisor (must be CS faculty). The MSCS Capstone project is advised by faculty in the Department of Computer Science.
Students in the MSCS program (Master’s in Computer Science) could choose a thesis option, instead of Capstone. The MS thesis option is designed to provide in-depth research opportunities with CS faculty. MENG does not provide a thesis option.
**DeepMind Fellowship For Computer Science Master’s Applicants Only for Fall 2023 (this fellowship is not applicable to MEngr applicants nor applicants in other programs/departments) **
The spirit of this fellowship is to support URM or women students who would otherwise not be able to pursue a graduate degree in AI/ML.
The fellowship will only be awarded to students who are offered and accept admission to the M.S. program in Computer Science at UCLA. To be eligible for this fellowship, you must satisfy ALL of the following requirements:
* You must apply to our MS program (deadline December 15, 2023). If admitted you must start the MS program Fall 2024 (you do not need to be admitted first to apply to the fellowship). If you are starting/have started the MS program before Fall 2023 you are not eligible to apply.
* You must reside in the United States (no exceptions) in Fall 2023 and for the duration of your M.S. study.
* You would be unable to take up the offer of admission to our program without financial assistance.
* You have a demonstrable interest in artificial intelligence and/or machine learning.
The intent of this fellowship is to provide access to higher education for students who might otherwise find it difficult or impossible to successfully pursue graduate study. In addition, individuals from cultural, racial, linguistic, geographic and socioeconomic backgrounds, including women, that are currently underrepresented in graduate education in the field of artificial intelligence and machine learning are especially encouraged to apply.
Deadline to apply is December 15, 2023.
To apply for this fellowship (the link will be live in mid September 2023) please visit:CS MS DeepMind Fellowship Application
**GRE Requirement for Fall 2024-2025 Admissions Cycle Only**
Students who wish to apply for admission to our graduate program for the 2024-2025 academic year (applications for this cycle are due December 15, 2023) are not required to take the GRE or submit a GRE score report as part of their application package. However, students may voluntarily submit GRE test scores and they will be reviewed as part of the holistic application consideration. The applications with GRE scores will not be given greater weight than those that do not include scores.
Graduate Student Affairs Office
UCLA Computer Science Department
Engineering VI Room 291
Los Angeles, CA 90095-1596
Graduate Student Affairs Officer (PhD program)
Phone: (310) 825-6830
Juliana Alvarez (MS program)
Graduate Student Affairs Officer
Phone: (310) 825-0060
Graduate Program Deadlines
Forms and Petitions for Graduate Students
Graduate Student Handbook
Graduate Student Resources
Job Announcements (for employers)
Additional Program Information (course descriptions)