Doctor of Philosophy in Computer Science - Artificial intelligence and Machine learning

The David R. Cheriton School of Computer Science has an international reputation in teaching, academics, research, and employment. We attract exceptional students from all over the world to study and conduct research with our award-winning faculty. You can participate in research projects in a wide variety of topics with our internationally acclaimed researchers. Our research spans the field of computer science, from core work on systems, theory and programming languages to human-computer interaction, DNA and quantum computing to theoretical and applied machine learning, just to name a few. As a graduate student, you will: Access research-intensive lab spaces. Gain the opportunity to publish your work in top conferences and journals. Present at premier conferences in front of peers, industry leaders, researchers, and experts in your field. As a graduate student, you will have the independence to pursue your preferred area of research with a faculty If you want to continue pursuing research and expand your learning, you will work with a supervisor to develop a thesis. As a graduate student at the PhD level you will be expected to conduct meaningful research that expands the scope of your graduate work.

Artificial intelligence and machine learning are broad research areas within computer science that encompass a number of topics related to the design of computer systems that perform tasks conventionally associated with human intelligence. These areas overlap with several other research areas both within and beyond computer science, including algorithm design, information theory, statistics, optimization, scientific computation, human-computer interaction, and more.
Machine learning is concerned with the analysis and development of methods to explore, discover, visualize, and model structure in data as well as to make predictions and decisions based on that structure. Data is often incomplete, noisy, non-homogeneous in structure and large in size (e.g., large number of observations or dimensions, or both). Special attention is paid to the development of computationally efficient (with respect to time and memory usage) algorithms. Research includes the mathematical and computational analysis of the statistical methodology, the development of new techniques, algorithms, and software, and the application of these to complex problems from other areas.

A Master's degree in Computer Science with a 78% average. Student with an undergraduate degree in Computer Science may apply for admission directly to the PhD program. Successful applicants will have an outstanding academic record, breadth of knowledge in computer science, and strong letters of recommendation. PhD applicants may be admitted into the Master of Mathematics (MMath) program. Like all MMath students, they will have the option to transfer into the PhD program before completing the master's thesis if their performance warrants. Resume Supplementary information form (SIF) The SIF contains questions specific to your program, typically about why you want to enrol and your experience in that field. Review the application documents web page for more information about this requirement If a statement or letter is required by your program, review the writing your personal statement resources for helpful tips and tricks on completion Transcript(s) References Three references are required; at least two academic Proof of English language proficiency, if applicable TOEFL 93 (writing 22, speaking 22), IELTS 6.5 (writing 6.0, speaking 6.5)