The Scripps Research Institute
The Doctor of Philosophy in Bioinformatics (PhD)is an interdisciplinary program that combines the application of computer technology to the management and analysis of biological data. The result is that computers are being used to organize data generated from experiments into databases, develop new algorithms and software, and use this software for the interpretation and analysis of the data into meaningful biological information. For the past ten years, our PhD program has been training students to organize, visualize, analyze and interpret biological data. Students have access to world renowned bioinformaticians at the University of British Columbia, Simon Fraser University and the BC Cancer Agency, and have exposure to the latest technologies to develop their skills.
Strategic Program Objectives:
The Bioinformatics PhD program integrates academic centres in computer science, statistics, molecular biology and biotechnology, with translational groups at hospitals and at the clinical interface. The innovative partnership among the University of British Columbia, Simon Fraser University and the BC Cancer Agency allows students' access to experts in the field of bioinformatics, and exposure to original research and opportunities to complete significant practical work on real bioinformatics problems. Internships allow student mobility between Canadian and international universities, institutions and industries to further enhance collaborations among Canadian high-technology research groups in both the private and public sectors.
The major requirement for the Ph.D. is completion of a research dissertation meeting the Faculty of Graduate and Postdoctoral Studies requirements. There are no specific course requirements for the Ph.D. degree program apart from the dissertation. However, the student's Ph.D. dissertation committee has the prerogative to impose course requirements where course deficiencies are perceived.
All doctoral students are required to successfully complete a comprehensive examination, which consists of an oral and written component within the first 36 months of study. All students are required to present a Bioinformatics graduate program seminar upon completion of their program, and before their dissertation defense.
A student's committee for the doctorate will consist of the dissertation supervisor and three others. The supervisor and at least one other member must be members of the Bioinformatics graduate program.
Students must secure a supervisor before they can be admitted into the program. As well, they must meet the minimum admission requirements set out by Graduate and Post-doctoral Studies at UBC.
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.
Students admitted to the Ph.D. degree program normally possess an M.Sc. degree in Bioinformatics or a related area, with clear evidence of research ability or potential.
CV, Official transcripts, three letters of reference, Official English exam scores (if 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.
Students who secure an NSERC-CREATE scholarship will undertake a 3-4 month internship that may be local, within Canada or at an international University or Institution.
Bioinformatics faculty are spread throughout the UBC campus, as well as off-campus at the BC Cancer Research Centre or hospital research labs and Institutions.
|Fees||Canadian Citizen / Permanent Resident / Refugee / Diplomat||International|
|Installments per year||3||3|
|Tuition per installment||$1,698.56||$2,984.09|
|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)||$969.17 (approx.)|
|Costs of living (yearly)||starting at $17,242.00 (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 students accepted by a faculty member and enrolled in the program will be paid a minimum stipend of $24,300/year. Applicants who are interested in the organization and management of data, the development of algorithms and software, and application of these approaches to questions in wide-ranging areas of biology may consider the NSERC-CREATE funded Training Program in High-Dimensional Bioinformatics that provides additional funding and professional development opportunities.
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.
12 students graduated between 2005 and 2013. Of these, career information was obtained for 12 alumni (based on research conducted between Feb-May 2016):
These statistics show data for the Doctor of Philosophy in Bioinformatics (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.
|2020||Dr. Grewal developed machine learning tools for cancer diagnosis and analysis. She found that when given large-scale genomic data, these methods can diagnose rare cancers and learn individual cancer biology. Her research shows that automated machine learning methods can enhance diagnostic and treatment decisions in precision oncology.|
|2020||Dr. Farahbod studied gene expression in human tissues and showed that observed patterns of expression can be attributed to the diverse cellular composition of the samples. By characterizing this feature of expression data, her study assists us in furthering our knowledge and understanding of the mechanisms behind the regulation of gene expression.|
|2020||Dr. Chu improved the process of using computers to extract meaningful information from biological sequences such as DNA. He designed computer programs to store data in probabilistic data structures, which purposely store data as approximate signatures in order to surpass the computational memory and speed limits of representing the data perfectly.|
|2020||Dr. Gatev developed a new method for analyzing epigenetic data to characterize genomic regions of concordant DNA methylation, which is an important part of the epigenome. His approach was used to characterize sex differences in DNA methylation of blood tissue. This work will improve statistical discovery and validation in future applications.|
|2019||Dr. Lever developed methods to extract biomedical knowledge from published academic papers. Working at BC Cancer's Genome Sciences Centre, he used machine learning approaches to find genetic information useful to clinicians treating cancer patients in a personalized way. His results are accessed daily by cancer researchers around the world.|
|2019||DNA sequencing machines read the A, C, G, and T nucleotides that compose chromosomes, but they read only short snippets of DNA and make errors. Dr. Jackman developed tools to reconstruct the true genome sequence from imperfect DNA sequencing reads. He used these tools to assemble the western red cedar genome, which is four times larger than the human genome.|
|2018||Dr. Shrestha developed computational algorithms to identify and prioritize cancer driver genes. He identified a novel molecular subtype of malignant peritoneal mesothelioma, potentially vulnerable to immunotherapy. His work helps clinicians contextualize genomic information in clinical decision making, thus enabling precision oncology.|
|2017||Dr. Shi created computer methods that identify which DNA sequence alterations impact the on/off switches for gene activity. This research will help us understand how each person's DNA increases or decreases the risk for health problems.|
|2017||Dr. Mohamadi designed and developed a collection of novel algorithms and software tools for the analysis of massive bioinformatics data. Theses algorithms and software tools are publicly available for free to facilitate research at health and life sciences laboratories and other organizations worldwide.|
|2017||Dr. Chan studied how tumours from lymphoma patients evolved over time under treatment. He identified markers of treatment resistance that can be used towards the design of future diagnostic tests. His work exemplifies the application of genomics in precision medicine.|