The School of Mathematical and Computational Sciences is seeking applications for Graduate Student Assistants in Computer Science and Statistics. 

RESPONSIBILITIES:

• The successful applicant may be required to provide online assistance to students enrolled in the associated courses in the form of responding to student questions and monitoring discussion boards
• The primary duty would be grading assignments in one or more of the following courses, depending on qualifications: 

CS-3420 Computer Communications

This course introduces the basic principles of modern computer communication: protocols, architectures, and standards. Topics include layered architectures, data transmission, error and flow control, medium access, routing, congestion control and common internet application protocols. Three lecture hours per week.

CS-3520 Operating Systems

This course introduces the student to the major concepts of modern operating systems. Topics covered include process management, memory management, file systems, device management and security. Three lecture hours per week.

CS-3610 Analysis, Design of Algorithms

This course, which introduces the study of algorithm design and measures of efficiency, is a continuation of CS 2610. Topics include algorithm complexity and analysis; techniques such as divide and conquer, greedy and dynamic programming; searching and sorting algorithms; graph algorithms; text processing; efficient algorithms for several common computer science problems and NP-completeness. Three lecture hours per week.

CS-4810 Software Engineering

This course emphasizes the theory, methods and tools employed in developing medium to large-scale software which is usable, efficient, maintainable, and dependable. Project planning and management are major foci. Topics include requirements modelling/specification, project costing, scheduling, software design, software architecture, traditional and agile process models, team management, and re-engineering. Students will develop a project plan for a major project to be undertaken in CS 4820 or CS 4830. Three lecture hours per week.

STAT-3240 Applied Regression Analysis

This course builds upon the basis of inference studied in Statistics 1910 and provides students with an advanced knowledge of regression techniques. Topics covered are simple and multiple linear regression techniques, matrix notation, the design matrix, model building techniques, residual analysis, and non-linear regression. Three lecture hours per week.

STAT-3910 Probability and Math Stats II

This course builds on the mathematical foundation developed in Statistics 2910 and introduces the student to the theory of statistical inference. Topics covered include sampling distributions and central limit theory, methods of estimation, hypothesis testing, least squares estimation of linear models, and an introduction to Bayesian inference. Three lecture hours per week.

QUALIFICATIONS: 

• Applicants should have completed an undergraduate degree in Mathematics, Statistics, Computer Science, or a related field.
• Must be currently enrolled in a  UPEI graduate program. 
• Applicants are expected to have completed undergraduate courses equivalent to those for which they are applying and demonstrated mastery of the course material.

Priority will be given to University of Prince Edward Island students in accordance with Recruitment, Selection, Hiring and Employment Policies and the Procedures manual.