Senior Director, Product & Business Development
PhD students in the Department of Computer Science may focus their research in the following areas:
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.
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.
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:
Overall score requirement: 100
Overall score requirement: 7.0
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.
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.
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.
Many programs require a statement of interest, sometimes called a "statement of intent", "description of research interests" or something similar.
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.
Permanent Residents of Canada must provide a clear photocopy of both sides of the Permanent Resident card.
All applicants must complete an online application form and pay the application fee to be considered for admission to UBC.
|Fees||Canadian Citizen / Permanent Resident / Refugee / Diplomat||International|
|Installments per year||3||3|
|Tuition per installment||$1,767.18||$3,104.64|
|Tuition per year|
(plus annual increase, usually 2%-5%)
|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)|
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.
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.
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.
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.
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.
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.
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.
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.
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.
Applicants have access to the cost calculator to develop a financial plan that takes into account various income sources and expenses.
111 students graduated between 2005 and 2013. Of these, career information was obtained for 106 alumni (based on research conducted between Feb-May 2016):
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.
|2016||People often behave in ways that are predictable, but which standard economic theory would call "irrational". Dr. Wright showed how to apply recent ideas from machine learning to this problem, developing algorithms that are optimized for people, rather than perfectly rational theoretical agents.|
|2016||Software tools mediate and shape users' behavior, constraining the way that people accomplish their tasks. Dr. Haraty studied and designed mechanisms that empower people to personalize their software by changing its functionality. Her design and the results of her empirical studies provide insights into the design of highly personalizable tools.|
|2016||Dr. Ding completed his doctoral studies in Computer Science. He developed computational algorithms to predict the mutations only in cancer, and further quantify the impacts of these mutations on gene expression. His research improves the potential of identifying the most important mutations in cancer for personalized, targeted therapy.|
|2016||Dr. Bessmeltsev introduced novel approaches to algorithmically infer artist-intended 3D shape from sketches. His methods interpret artist drawings and create the envisioned 3D CAD or character models.|
|2016||Dr. Shahriari contributed to the increasingly relevant field of Bayesian optimization and sequential experimental design. His work explores automatically tuning experiments in order to avoid tedious labour often reserved for graduate students, lab technicians, and other highly qualified personel.|
|2016||Dr. Lu studied social influence and its applications in viral marketing and recommender systems from a computational perspective. He proposed mathematical models to encode complex social interactions and designed algorithms to efficiently and effectively tackle influence maximization problems in such contexts.|
|2016||Dr. Izsak studied sheaves on graphs, which similar to maps, are tools that help track data. Her research resulted in several foundational theorems and answered a question about the difficulty of checking an important sheaf property. Her results are useful in the study of open problems in group theory, graph theory and computational complexity.|
|2016||Dr. Edwards developed numerical methods for the physical simulation of fluids. His work improves upon the accuracy and efficiency of previous methods. Applied to computer graphics, this work help to improve what is possible in special effects.|
|2016||Dr. Macedo developed novel mathematical tools and numerical algorithms for the solution of optimizing problems arising in scientific imaging. His work outlines a nonstandard theoretical approach to such problems as well as a concrete computational realization capable of solving large scale instances in practical scenarios.|
|2016||Dr. Brehmer studied why and how people use data visualization tools and techniques to process information. He introduced a framework for classifying visualization tasks and used it to conduct design and evaluation projects in the domains of journalism and energy management. His research can be applied when developing new data visualization tools.|
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).