APTPUO - Spring / Summer 2026 - GEG4120-A00

Description

: Spatial data science is useful in many fields, including big data, population health sciences, biological sciences, earth sciences, medicine, engineering and social sciences. In this course, you will learn how to manipulate, analyze and model spatial data. Sections of the course focus on stochastic simulation and Monte Carlo methods in point-pattern analysis, spatial autocorrelation and geostatistics. Practical applications utilize the open-source software and data science computing languages (e.g. R, Python), no previous experience required. At the end of this course, you will have a toolbox of spatial analytical skills and a solid understanding of their appropriate applications to real-world questions.

Posting limited to :

Professeur à temps-partiel étudiant  / Student Part-Time Professor

Date Posted (YYYY / MM / DD) :

2026 / 02 / 16

Applications must be received BEFORE (YYYY / MM / DD) :

2026 / 03 / 19

Expected Enrolment : 20

Approval date : 2026 / 02 / 16

Number of credits : Work Hours :

39

Hourly Rate :

Enseignement / Teaching : $239.47 (2024-2025)

The academic year starts on September 1 and ends on August 31.

These rates do not included vacation pay nor statutory pay.

These rates will be applied until a new collective agreement is ratified. Retro will be paid after the ratification.

Course type : Posting type :

Régulier / Regular

Language of instruction :

Anglais | English

Competence in second language :

N / A

Course Schedule :

Mardi | Tuesday 14 : 30-17 : 30 Jeudi | Thursday 14 : 30-17 : 30 -

Requirements : Requirements

M.A. or M.Sc. in geography, environmental studies, or related discipline. Experience with GIS, remote sensing, spatial data analysis, and programming for geospatial data processing. An acceptable level of education / experience could be viewed as being equivalent to the educational requirement and / or demonstrated experience

Course and exam dates

Course : June 22 to July 31

Exam : August 4 to 6

Additional Information and / or Comments :

An acceptable level of education and / or experience could be viewed as being equivalent to the educational required and / or demonstrated experience.