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Masters in Computational Science

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Overview

Academic disciplines of chemistry, chemical biology, biophysics and chemical physics have a critical dependence on computer simulation and large scale data analysis to understand observed phenomena and advance the frontiers of disciplinary knowledge. This course aims to prepare students in the methodology required to undertake research in computational science as applied to chemistry, chemical biology, biophysics and chemical physics. The two streams of focus are computation and informatics. The course will commence with project assignment followed by a combination of in-house and online training short (non-credit) courses in: Scientific Computing, High Performance Computing, Computational Methods for Data Analysis, Data Management, R programming, Quantum Mechanics and Statistical Mechanics. The above short training courses are designed to prepare students to successfully complete a computational science project and dissertation.

Aims

Training in scripting, mathematical modelling and informatics methods as it applies to the domain sciences (chemistry, chemical biology, glycobiology, genomics, glycomics, biophysics, and chemical physics). Develop research methodology competence through the investigation of a substantial problem in the domain sciences requiring a computational approach. The research methods are exclusively the development of a new computational method or modelling (statistical & mathematical) of a problem in the domain sciences.

Outcomes

Produce a dissertation that demonstrates competence and an understanding in computational methods relating to an assigned (by the research supervisor) problem in the domain science. Perform research that illustrates the ability to develop a computational method and/or to solve a modelling or informatics problem in a domain science. Producing Scientific Computer Code in one of the following programming languages: C++, Fortran, C AND/OR design a computational module in scripting languages Python or PERL AND/OR apply or design an analytics method using R, SQL, MATLAB or MAPLE.