Doctor of Philosophy in Computer Science (PhD)

Overview

PhD students in the Department of Computer Science may focus their research in the following areas:

  • Artificial Intelligence: computer vision, decision theory/game theory, knowledge representation and reasoning, intelligent user interfaces, machine learning, natural language understanding and generation, robotics and haptics.
  • Computer Graphics: animation, imaging, modeling, rendering, visualization.
  • Data Management and Mining: business intelligence, data integration, genomic analysis, text mining, web databases.
  • Formal Verification and Analysis of Systems: analog, digital and hybrid systems, VLSI, protocols, software.
  • Human Centered Technologies: human computer interaction (HCI), visual, haptic and multimodal interfaces, computer-supported cooperative work (CSCW), visual analytics.
  • Networks, Systems, and Security: high performance computing/parallel processing, networking, operating systems and virtualization, security.
  • Scientific Computing: numerical methods and software, differential equations, linear algebra, optimization.
  • Software Engineering and Programming Languages: development tools, foundations of computation, middleware, programming languages, software engineering.
  • Theory: algorithm design and analysis (including empirical), algorithmic game theory, discrete optimization, graph theory, computational geometry

What makes the program unique?

The UBC Department of Computer Science has many contacts in the computing industry. A strong rapport between the industry and research communities is beneficial to both, especially in cases where the department focuses its research to developing real-world applications.

 

Program Enquiries

Still have questions after reviewing this page thoroughly?
Contact the program

Admission Information & Requirements

1) Check Eligibility

Minimum Academic Requirements

The Faculty of Graduate and Postdoctoral Studies establishes the minimum admission requirements common to all applicants, usually a minimum overall average in the B+ range (76% at UBC). The graduate program that you are applying to may have additional requirements. Please review the specific requirements for applicants with credentials from institutions in:

Each program may set higher academic minimum requirements. Please review the program website carefully to understand the program requirements. Meeting the minimum requirements does not guarantee admission as it is a competitive process.

English Language Test

Applicants from a university outside Canada in which English is not the primary language of instruction must provide results of an English language proficiency examination as part of their application. Tests must have been taken within the last 24 months at the time of submission of your application.

Minimum requirements for the two most common English language proficiency tests to apply to this program are listed below:

TOEFL: Test of English as a Foreign Language - internet-based

Overall score requirement: 100

Reading

22

Writing

21

Speaking

21

Listening

22

IELTS: International English Language Testing System

Overall score requirement: 7.0

Reading

6.5

Writing

6.5

Speaking

6.5

Listening

6.5

Other Test Scores

Some programs require additional test scores such as the Graduate Record Examination (GRE) or the Graduate Management Test (GMAT). The requirements for this program are:

The GRE is not required.

2) Meet Deadlines

Application open dates and deadlines for an upcoming intake have not yet been configured in the admissions system. Please check back later.

3) Prepare Application

Transcripts

All applicants have to submit transcripts from all past post-secondary study. Document submission requirements depend on whether your institution of study is within Canada or outside of Canada.

Letters of Reference

A minimum of three references are required for application to graduate programs at UBC. References should be requested from individuals who are prepared to provide a report on your academic ability and qualifications.

Statement of Interest

Many programs require a statement of interest, sometimes called a "statement of intent", "description of research interests" or something similar.

Supervision

Students in research-based programs usually require a faculty member to function as their supervisor. Please follow the instructions provided by each program whether applicants should contact faculty members.

Instructions regarding supervisor contact for Doctor of Philosophy in Computer Science (PhD)
Applicants should browse faculty profiles and indicate in their application who they are interested in working with. No commitment from a supervisor prior to applying is necessary, but contacting faculty members is encouraged.

Citizenship Verification

Permanent Residents of Canada must provide a clear photocopy of both sides of the Permanent Resident card.

4) Apply Online

All applicants must complete an online application form and pay the application fee to be considered for admission to UBC.

Tuition & Financial Support

Tuition

FeesCanadian Citizen / Permanent Resident / Refugee / DiplomatInternational
Application Fee$110.00$168.25
Tuition *
Installments per year33
Tuition per installment$1,767.18$3,104.64
Tuition per year
(plus annual increase, usually 2%-5%)
$5,301.54$9,313.92
Int. Tuition Award (ITA) per year (if eligible) $3,200.00 (-)
Other Fees and Costs
Student Fees (yearly)$1,057.05 (approx.)
Costs of living (yearly)starting at $17,366.20 (check cost calculator)
* Regular, full-time tuition. For on-leave, extension, continuing or part time (if applicable) fees see UBC Calendar.
All fees for the year are subject to adjustment and UBC reserves the right to change any fees without notice at any time, including tuition and student fees. Tuition fees are reviewed annually by the UBC Board of Governors. In recent years, tuition increases have been 2% for continuing domestic students and between 2% and 5% for continuing international students. New students may see higher increases in tuition. Admitted students who defer their admission are subject to the potentially higher tuition fees for incoming students effective at the later program start date. In case of a discrepancy between this webpage and the UBC Calendar, the UBC Calendar entry will be held to be correct.

Financial Support

Applicants to UBC have access to a variety of funding options, including merit-based (i.e. based on your academic performance) and need-based (i.e. based on your financial situation) opportunities.

Program Funding Packages

All full-time PhD students will be provided with a funding package of at least $24,000 for each of the first four years of their PhD program. The funding package consists of any combination of internal or external awards, teaching-related work, research assistantships, and graduate academic assistantships.  This support is contingent on full-time registration as a UBC Graduate student, satisfactory performance in assigned teaching and research assistantship duties, and good standing with satisfactory progress in your academic performance. CS students are expected to apply for fellowships or scholarship to which they are eligible. 

UBC has launched Canada's first Blockchain training pathway for graduate students. The Graduate Pathway on Blockchain and Decentralized Trust Technologies will be a 12-credit non-degree training program that augments existing Master's and Phd programs. Additional funding may be available for students as part of the Blockchain pathway.

Average Funding
Based on the criteria outlined below, 66 students within this program were included in this study because they received funding through UBC in the form of teaching, research/academic assistantships or internal or external awards averaging $30,611.
  • 32 students received Teaching Assistantships. Average TA funding based on 32 students was $5,590.
  • 63 students received Research/Academic Assistantships. Average RA/AA funding based on 63 students was $17,310.
  • 64 students received internal awards. Average internal award funding based on 64 students was $10,247.
  • 7 students received external awards. Average external award funding based on 7 students was $23,476.

Study Period: Sep 2020 to Aug 2021 - average funding for full-time PhD students enrolled in three terms per academic year in this program across years 1-4, the period covered by UBC's Minimum Funding Guarantee. Averages might mask variability in sources and amounts of funding received by individual students. Beyond year 4, funding packages become even more individualized.
Review methodology
Scholarships & awards (merit-based funding)

All applicants are encouraged to review the awards listing to identify potential opportunities to fund their graduate education. The database lists merit-based scholarships and awards and allows for filtering by various criteria, such as domestic vs. international or degree level.

Teaching Assistantships (GTA)

Graduate programs may have Teaching Assistantships available for registered full-time graduate students. Full teaching assistantships involve 12 hours work per week in preparation, lecturing, or laboratory instruction although many graduate programs offer partial TA appointments at less than 12 hours per week. Teaching assistantship rates are set by collective bargaining between the University and the Teaching Assistants' Union.

Research Assistantships (GRA)

Many professors are able to provide Research Assistantships (GRA) from their research grants to support full-time graduate students studying under their direction. The duties usually constitute part of the student's graduate degree requirements. A Graduate Research Assistantship is a form of financial support for a period of graduate study and is, therefore, not covered by a collective agreement. Unlike other forms of fellowship support for graduate students, the amount of a GRA is neither fixed nor subject to a university-wide formula. The stipend amounts vary widely, and are dependent on the field of study and the type of research grant from which the assistantship is being funded. Some research projects also require targeted research assistance and thus hire graduate students on an hourly basis.

Financial aid (need-based funding)

Canadian and US applicants may qualify for governmental loans to finance their studies. Please review eligibility and types of loans.

All students may be able to access private sector or bank loans.

Foreign government scholarships

Many foreign governments provide support to their citizens in pursuing education abroad. International applicants should check the various governmental resources in their home country, such as the Department of Education, for available scholarships.

Working while studying

The possibility to pursue work to supplement income may depend on the demands the program has on students. It should be carefully weighed if work leads to prolonged program durations or whether work placements can be meaningfully embedded into a program.

International students enrolled as full-time students with a valid study permit can work on campus for unlimited hours and work off-campus for no more than 20 hours a week.

A good starting point to explore student jobs is the UBC Work Learn program or a Co-Op placement.

Tax credits and RRSP withdrawals

Students with taxable income in Canada may be able to claim federal or provincial tax credits.

Canadian residents with RRSP accounts may be able to use the Lifelong Learning Plan (LLP) which allows students to withdraw amounts from their registered retirement savings plan (RRSPs) to finance full-time training or education for themselves or their partner.

Please review Filing taxes in Canada on the student services website for more information.

Cost Calculator

Applicants have access to the cost calculator to develop a financial plan that takes into account various income sources and expenses.

Career Outcomes

111 students graduated between 2005 and 2013. Of these, career information was obtained for 106 alumni (based on research conducted between Feb-May 2016):


RI (Research-Intensive) Faculty: typically tenure-track faculty positions (equivalent of the North American Assistant Professor, Associate Professor, and Professor positions) in PhD-granting institutions
TI (Teaching-Intensive) Faculty: typically full-time faculty positions in colleges or in institutions not granting PhDs, and teaching faculty at PhD-granting institutions
Term Faculty: faculty in term appointments (e.g. sessional lecturers, visiting assistant professors, etc.)
Sample Employers in Higher Education
University of British Columbia (5)
McGill University (3)
University of Waterloo (3)
University of Manitoba (2)
Swansea University
Stanford University
University of Utah
Ecole Polytechnique Federale de Lausanne (EPFL)
Swiss Federal Institute of Technology
University of Saskatchewan
Sample Employers Outside Higher Education
Google (12)
Microsoft (4)
Amazon (3)
Intel Corporation (3)
Disney (2)
Oracle Labs (2)
IBM (2)
Tasktop Technologies (2)
Tableau (2)
OriGene Technologies Inc.
Sample Job Titles Outside Higher Education
Research Scientist (5)
Software Engineer (5)
Senior Software Engineer (4)
Chief Technology Officer (3)
Product Manager (3)
Software Development Engineer (2)
Senior Data Scientist (2)
Senior Research Engineer (2)
Advisory Engineer
Senior Research Scientist
PhD Career Outcome Survey
You may view the full report on career outcomes of UBC PhD graduates on outcomes.grad.ubc.ca.
Disclaimer
These data represent historical employment information and do not guarantee future employment prospects for graduates of this program. They are for informational purposes only. Data were collected through either alumni surveys or internet research.

Enrolment, Duration & Other Stats

These statistics show data for the Doctor of Philosophy in Computer Science (PhD). Data are separated for each degree program combination. You may view data for other degree options in the respective program profile.

Enrolment Data

 20212020201920182017
Applications357291269246151
Offers4049262216
New registrations2024161313
Total enrolment120106897876

Completion Rates & Times

This program has a graduation rate of 72% based on 43 students admitted between 2008 - 2011. Based on 30 graduations between 2017 - 2020 the minimum time to completion is 3.33 years and the maximum time is 9.00 years with an average of 5.77 years of study. All calculations exclude leave times.
Disclaimer
Admissions data refer to all UBC Vancouver applications, offers, new registrants for each year, May to April [data updated: 7 April 2022]. Enrolment data are based on March 1 snapshots. Program completion data are only provided for datasets comprised of more than 4 individuals. Rates and times of completion depend on a number of variables (e.g. curriculum requirements, student funding), some of which may have changed in recent years for some programs [data updated: 19 October 2021].

Research Supervisors

This list shows faculty members with full supervisory privileges who are affiliated with this program. It is not a comprehensive list of all potential supervisors as faculty from other programs or faculty members without full supervisory privileges can request approvals to supervise graduate students in this program.

  • Mehta, Aastha (Networking, Security & Privacy, Systems security, Data privacy, Operating systems, Distributed systems)
  • Mitchell, Ian (safety critical systems, assistive technology (mobility), robotics, scientific computing, cyber-physical systems, Mathematical software, computational science and engineering, hybrid and cyber-physical systems, verification and validation, reproducible research, level set methods, robotic path, planning)
  • Munzner, Tamara (Human-centered computing; visualization; information visualization; visual analytics; data science)
  • Murphy, Gail (Computer and information sciences; Software Development; knowledge worker productivity; software design; software engineering; software evolution)
  • Ng, Raymond Tak-yan (Data mining and analysis, health informatics, text summarization, text mining)
  • Pai, Dinesh (Robotics, computer graphics, medical imaging, neuroscience, sensorimotor computation )
  • Park, Mi Jung (Privacy-preserving machine learning algorithms, Compressing neural network models using Bayesian methods, Relationships between differential privacy and other emerging notions in machine learning)
  • Pasquier, Thomas (Development of more transparent computer systems, Whole-system provenance, Computational experiments reproducibility, Intrusion detection, privacy and compliance)
  • Poole, David (Computer and information sciences; Artificial Intelligence; Decision Analysis; Knowledge Representation; Machine Learning; Preference Elicitation; Probabilistic Graphical Models; Reasoning under Uncertainty; Relational Learning)
  • Pottinger, Rachel (Computer and information sciences; Computer Science and Statistics; data integration; data management; databases; metadata management)
  • Rhodin, Helge (Computer and information sciences; Shape Recognition and Computer Graphics; Virtual Reality; Neuronal Systems; computer graphics; Computer Vision; Machine Learning)
  • Roth, Andrew (Molecular Oncology; Bioinformatics; Computational Biology; computational statistics; Machine Learning; genomics; Cancer Evolution; Evolutionary cancer biology; Cancer omics data; computational methods for studying clonal population structures and tumour evolution; Methodological work in computational statistics)
  • Schmidt, Mark (Machine learning; Numerical Optimizaiton; Probabilistic Graphical Models; Causality)
  • Seltzer, Margo (Computer Systems; Data Quality; Storage; Machine Learning & Systems; Systems for capturing and accessing data provenance; File Systems; databases; Transaction processing systems; Storage and analysis of graph-structured data; New architectures for parallelizing execution; Systems that apply technology to problems in healthcare.; Artificial Intelligence; Decision-making & Action; Software Practices; Networks, Systems and Security)
  • Sheffer, Alla (Computer graphics, shape modeling and geometry processing)
  • Shepherd, Bruce (algorithms, optimization, convex geometry, and graph theory)
  • Shwartz, Vered (Artificial Intelligence; Machine Learning; Natural Language Processing)
  • Sigal, Leonid (Computer and information sciences; Artificial Intelligence; Computer Science and Statistics; Parametric and Non-Parametric Inference; Computer Vision; Machine Learning; Semantic Recognition; Vision + Natural Language Processing; Visual Recognition and Understanding)
  • Van de Panne, Michiel (Computer Science and Statistics; Computer Sciences and Mathematical Tools; Robotics and Automation; simulation of human movement; computer animation; Robotics; deep reinforcement learning; motor control; computer graphics)
  • Wagner, Alan (Parallel computation, interconnection networks, parallel programming environments)
  • Wood, Frank Donald (Computer and information sciences; Artificial Intelligence; Computational neuroscience; Machine Learning; Natural Language Processing; New models and inference algorithms; Probabilistic models; Probabilistic programming; Probabilistic programming systems; Reinforcement learning; Robotics; vision)
  • Xiao, Robert (human-computer interaction; Virtual/augmented reality)
  • Yi, Kwang Moo (Computer vision in artificial intelligence; Pattern recognition and artificial vision; Computer Vision; Machine Learning; Visual Geometry; Astronomy; Biomedical imaging)

Pages

Doctoral Citations

A doctoral citation summarizes the nature of the independent research, provides a high-level overview of the study, states the significance of the work and says who will benefit from the findings in clear, non-specialized language, so that members of a lay audience will understand it.
Year Citation
2020 Dr. Babanezhad's research explored optimizing parameters for machine learning algorithms, like those used in data processing, focusing specifically on computational cost. His proposed method, which he has tested on a new set of constraints and machine learning models, can train models in less time and achieve better results than previous methods.
2020 Dr. Chen studied numerical algorithms for stiff elastodynamic simulation, a key procedure in computer graphics applications. He developed models for natural physical movements that would maintain stability and produce lively simulations at a lower cost. This work will improve the efficiency and accuracy for physically-based computer simulation.
2020 Dr. Zolaktaf examined ways of improving user interaction with data that is stored in large structured data sources. She developed algorithms and models that help users to explore, query, and analyze data more efficiently.
2019 Dr. Toker's research on user-adaptive information visualizations is at the intersection of Artificial Intelligence and Human Computer Interaction. His work leveraged eye tracking to show how adaptive interventions could be devised to support users according to their individual needs and differences.
2019 Dr. Sachdeva designed techniques for biomechanical simulation of the human hand. He modelled the dynamics of tendons wrapped on bones. He developed anatomical simulation software capable of modelling human hand function driven by muscles. Such a model may be used to explain the role of different muscles and ligaments in coordinating movement.
2019 Dr. Crisan examined how 'big data' used by public health systems should be visually represented for decision making. She developed software tools and methods that can help people analyze, see, and understand complex data used to monitor and control disease outbreaks.
2019 Dr. Kazemi explored how machine learning can be applied to worlds composed of objects and relations. He devised models and facilitated computational techniques that use data about objects to make predictions about their properties and relations. His work can be used in applications where the underlying data is in the form of a graph.
2019 Dr. Berseth developed new methods for controlling the movement of simulated characters and robots. Using machine learning methods, he developed control structures that allow for more efficient learning as well as the integration of multiple motion skills.
2019 Dr. Nanavati examined how modern high-performance servers can safely be shared across multiple applications. He then developed systems that enabled high resource efficiency on these shared servers, while isolating applications and providing them with virtual hardware abstractions, all with performance comparable to dedicated hardware.
2019 Dr. Martinez-Covarrubias developed compression algorithms for very large databases of high-dimensional vectors. The compressed database can be used to speed up search using a variety of similarity measures. These algorithms can be used in image search engines, recommender systems, or machine learning algorithms.

Pages

Further Information

Specialization

Computer Science covers Bayesian statistics and applications, bioinformatics, computational intelligence (computational vision, automated reasoning, multi-agent systems, intelligent interfaces, and machine learning), computer communications, databases, distributed and parallel systems, empirical analysis of algorithms, computer graphics, human-computer interaction, hybrid systems, integrated systems design, networks, network security, networking and multimedia, numerical methods and geometry in computer graphics, operating systems, programming languages, robotics, scientific computation, software engineering, visualization, and theoretical aspects of computer science (computational complexity, computational geometry, analysis of complex graphs, and parallel processing).

Faculty Overview

Program Identifier

VGDPHD-FM
 
 
 
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