Postdoctoral Fellow Sessional Instructors: Department of Mathematics and Statistics

Description

The Department of Mathematics & Statistics in the Faculty of Science at the University of Calgary is inviting applications for the Fall 2026 - Summer 2027 Sessional Instructor ships for individuals applying to or holding a Postdoctoral appointment within the Department of Mathematics and Statistics.

The successful candidates will have responsibilities for lecture instruction, lab co-ordination, and any other associated duties, for up to two of these courses offered during the Fall 2026, Winter 2027, Spring 2027 and/or Summer 2027.

The Department of Mathematics & Statistics in the Faculty of Science at the University of Calgary is looking for instructors for the following courses. All course components will be delivered in-person.

DATA 602 -
Statistical Data Analysis
An introduction to the foundations of statistical inference including probability models for data analysis, classical and simulation-based statistical inference, and implementation of statistical models with R.

DATA 603 -
Statistical Modelling with Data
An introduction to the creation of complex statistical models, including exposure to multivariate model selection, prediction, the statistical design of experiments and analysis of data in R.

MATH 211 -
Linear Methods I
An introduction to systems of linear equations, vectors in Euclidean space and matrix algebra. Additional topics include linear transformations, determinants, complex numbers, eigenvalues, and applications.

MATH 249 -
Introductory Calculus
An introduction to single variable calculus. Limits, derivatives and integrals of algebraic, exponential, logarithmic and trigonometric functions play a central role. Additional topics include applications of differentiation, the fundamental theorem of calculus, improper integrals and applications of integration.

MATH 265 -
University Calculus I
An introduction to single variable calculus intended for students with credit in high school calculus. Limits, derivatives, and integrals of algebraic, exponential, logarithmic and trigonometric functions play a central role. Additional topics include applications of differentiation; the fundamental theorem of calculus, improper integrals and applications of integration. Differential calculus in several variables will also be introduced.

MATH 267 -
University Calculus II
A concluding treatment of single variable calculus and an introduction to calculus in several variables. Single variable calculus: techniques of integration, sequences, series, convergence tests, and Taylor series. Calculus of several variables: partial differentiation, multiple integration, parametric equations, and applications.

MATH 271 -
Discrete Mathematics
An introduction to proof techniques and abstract mathematical reasoning: sets, relations and functions; mathematical induction; integers, primes, divisibility and modular arithmetic; counting and combinatorics; elements of probability, discrete random variables and Bayes' theorem.

MATH 275 -
Calculus for Engineers and Scientists
An extensive treatment of differential and integral calculus in a single variable, with an emphasis on applications. Differentiation: derivative laws, the mean value theorem, optimization, curve sketching and other applications. Integral calculus: the fundamental theorem of calculus, techniques of integration, improper integrals, and areas of planar regions. Infinite series: power series, Taylor's theorem and Taylor series.

MATH 277 -
Multi-variable Calculus for Engineers and Scientists
An introduction to calculus of several real variables: curves and parametrizations, partial differentiation, the chain rule, implicit functions; integration in two and three variables and applications; optimization and Lagrange multipliers.

MATH 311 -
Linear Methods II
An introductory course in the theory of abstract vector spaces: linear independence, spanning sets, basis and dimension; linear transformations and the rank-nullity theorem; the Gram-Schmidt algorithm and orthogonal diagonalization; and other applications.

MATH 375 -
Differential Equations for Engineers and Scientists
Definition, existence and uniqueness of solutions; first order and higher order equations and applications;
Homogeneous systems;
Laplace transform; partial differential equations of mathematical physics.

STAT 205 -
Introduction to Statistical Inquiry
The systematic progression of statistical principles needed to conduct a statistical investigation culminating in parameter estimation, hypothesis testing, statistical modelling, and design of experiments.

STAT 213 -
Introduction to Statistics I
Introduction to probability, including Bayes' law, expectations and distributions. Discrete and continuous random variables, including properties of the normal curve. Collection and visual display of single and multi-dimensional data. Introduction to statistical modelling and estimation. Parametric and simulation-based confidence interval estimation.

STAT 217 -
Introduction to Statistics II
Parametric and simulation-based…