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.
During my Master's degree I came to Vancouver for an 8-month internship. Interacting with students and alumni from UBC and learning about the research opportunities, I realized a great potential fit. The strong group of renowned researchers in the fields of Machine-Learning and NLP made UBC the ideal place to start my Ph.D.
UBC’s Faculty of Science is home to an array of outstanding scientists and students who strive to unravel the principles that underlie our universe - from the subatomic to the macroscopic, from pure mathematics to biotechnology, from ecosystems to galactic systems. In this session hosted by Professor Mark MacLachlan, Associate Dean of Research & Graduate Studies, we’ll hear from faculty members and graduate students on some of the exciting research happening within the Faculty of Science. We’ll also take a look at the wide range of graduate programs available, what it's like to be a grad student in Science, and also provide some application advice. Be sure to join us and get an insight into how UBC Science is discovering new scientific knowledge and preparing Canada’s and the world’s next generation of scientists.
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||$1,732.53||$3,043.77|
|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)||$1,052.34 (approx.)|
|Costs of living (yearly)||starting at $17,126.20 (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.
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.
|2021||Many of the artificial-intelligence-powered products that we use daily rely on a family of methods called "deep learning"'. Dr. Shafaei presented solutions that enable a broader and safer application of these techniques. He also introduced a new application of deep learning for automated portrait editing that produces high-quality images.|
|2021||Dr. Zolaktaf studied ways to improve the prediction of nucleic acid kinetics. This study provides more efficient computational methods for predicting nucleic acid kinetics and improving the underlying kinetic models for nucleic acids. Her contributions will make it easier to design nucleic-acid based devices, such as DNA robots.|
|2021||Dr. Yang developed recommender systems to unveil binding preferences of experimentally unexplored RNA-binding proteins. He utilized cutting-edge deep learning techniques in the systems to improve the understanding of such proteins and to provide new opportunities to investigate the complex post-transcriptional regulations.|
|2020||Dr. Best created a synthesis of techniques from disparate areas of Systems and Programming Languages research, augmented with new highly efficient coordination algorithms, to better leverage the multiple processors available in modern computing devices. This work will open new avenues for programmers to write faster programs with fewer errors.|
|2020||Dr. Liaw explored machine learning from the lens of theoretical computer science. He developed new algorithms with strong theoretical guarantees for online decision making and distribution learning. His contributions may be applied to develop learning algorithms with improved error guarantees while requiring sufficiently less data.|
|2020||Dr. Vitale studied how everyday technology users curate their personal data, such as photos, documents, or mobile apps, by deciding what to keep or discard. His work characterizes the strong individual differences that users display in their decisions and provides implications for designing personalized tools that can meet different user needs.|
|2020||Dr. Dorri explored methods for detecting genetic mutations with a resolution down to one cell. The accumulation of genetic mutations disrupts regular cell activity and leads to tumour development. Her findings can be applied to the study of clonal dynamics in tumours, which can potentially lead to enhanced cancer diagnosis and treatment.|
|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.|
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).
UBC offers a very rich environment for interdisciplinary research and has an excellent reputation for producing world class results in numerical methods, computer graphics and computational mechanics. These resources are particularly relevant to my area of research. In addition, the landscape...
I applied to a few different schools and spoke with several different professors who had expressed interest in working with me. In the end, I made the decision for a number of reasons. First, I found the research of my potential supervisor at UBC the most interesting and relevant to important, real...