Doctor of Philosophy in Applied Mathematics - Scientific Computing

Modern society has been shaped by a long tradition of mutual inspiration and enrichment between Mathematics and the Sciences. In this tradition, the Department of Applied Mathematics offers its graduate students opportunities for study in the areas of Control Theory and Dynamical Systems, Fluid Mechanics, Mathematical Medicine and Biology, Mathematical Physics, and Scientific Computation. Our students' research projects involve cutting-edge applications of mathematical theory in a broad range of fundamental and applied sciences. These applications include, for instance, cancer therapy optimization, control of shape memory alloys, fractal image processing, quantum computing, and the study of climate variability, inflationary cosmology, and nanotechnology. The Department of Applied Mathematics is one of five units that comprise the Faculty of Mathematics at the University of Waterloo, which was ranked 20th worldwide in the 2015 QS University Rankings for mathematics. Graduate students in the department benefit from our close links with the Faculties of Science and Engineering, the Centre for Mathematical Medicine, the Centre for Theoretical Neuroscience, the Institute for Quantum Computing, the Perimeter Institute for Theoretical Physics, the Waterloo Institute for Nanotechnology, the Water Institute, and the Centre for Computational Mathematics in Industry and Commerce. We offer both Master's and PhD programs. Our thesis-based Master's of Mathematics (MMath) program normally takes two years to complete. Many of the graduates of this program subsequently pursue PhD degrees, others are successful in obtaining rewarding positions in industry or government. Our PhD program generally takes four years to complete. Most of our PhD graduates find employment in university research. Others take on positions in research and development in industry, government, or commerce.
Traditional areas of strength in Scientific Computing research in the department include numerical methods for PDEs and numerical linear algebra. Research is also conducted in other areas of Scientific Computing, such as numerical methods for ODEs, inverse problems and numerical optimization. Research in Scientific Computing involves a variety of methods and techniques, ranging from the development and mathematical analysis of numerical algorithms to advanced implementations on parallel supercomputers and GPUs. There are frequent research interactions and joint graduate courses in the Scientific Computing field with Waterloo's School of Computer Science, Department of Combinatorics and Optimization, and Centre for Computational Mathematics. Large-scale computing infrastructure is provided by SHARCNET and Compute Canada.

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