Statistical Bioinformatics

for Teaching Assistants, Graduates Service Assistants & Sessional Lecturers

Teaching Assistant Work Assignment

Type of Work Assignment and Bargaining Unit:

GTA, Unit 1

Academic Unit:

Integrative Biology

Semester(s) of Assignment(s):

Winter 2027

This Work Assignment(s) may be assigned to fulfill the terms and conditions of a guaranteed Job Security Period:

Some

Course Number:

BINF
* 6970

Course Name:

Statistical Bioinformatics

Course Format:

In-Class

Course

Description:

See Course Calendar

TBD

Level of Appointment for GTA, GSA-1 UTA(s)

The following is an estimate of number and levels of available appointments at the time of posting. This may change (increase or decrease) at the time of assignment contingent on departmental needs.

This Posting includes Multiple Work Assignments:

No

Number of Available 0.25 (35 hour) Work Assignments:

0

Number of Available 0.5 (70 hour) Work Assignments:

1

Number of Available 0.75 (105 hour) Work Assignments:

0

Number of Available Full 1.0 (140 hour) Work Assignments:

0

Total Number (Load) of Assignment(s) Available:

1

Duties and Responsibilities

Anticipated

Duties and Responsibilities:

Orientation-Training

Office Hours

Preparation

Student Consultation

Conducting Labs/Seminars

Meetings

Invigilating Exams

Grading

Qualifications

Required Qualifications:

Must hold a Master of Bioinformatics or MSc in Bioinformatics degree or similar qualification (e.g. PhD transfer student who has completed the Masters-level bioinformatics coursework). Must have demonstrable knowledge of advanced statistical concepts and techniques, e.g., regression models including logistic regression, clustering and classification. Must have strong programming and analysis skills in the R language and RStudio work environment, and comfort in employing data manipulation and visualization tools in R (e.g. ggplot2).

Must have strong oral communication skills, as the TA will hold office hours to assist students with their course assignments. Must have strong attention to detail and conduct consistent grading of coding and statistical assignments. Must possess strong time management skills and be able to complete grading to deadlines and provide written feedback to students. By applying for this TA position, you are agreeing to be on campus and available from the start of the contract (January 7, 2027) to complete all assigned duties, available to attend all mandatory meetings, invigilation of IB exams as assigned, grade mid-term exams/papers, and be available to the end of the contract (May 7, 2027) to grade final exams/papers.

Days Required and Wages

Days and Times

Required:

TBD

Period of the Work Assignment (Start Date and End Date):

January 7, 2027 to May 7, 2027

Wage Rate (per hour, per semester, per Full-load 1.0 Work Assignment):

Other Posting Information

Final date to receive applications (All postings will automatically expire at 11:59 pm on this day):

Thursday, November 12, 2026

At the University of Guelph, fostering a culture of inclusion is an institutional imperative. The University invites and encourages applications from all qualified individuals, including from groups that are traditionally underrepresented in employment, who may contribute to further diversification of our Institution. For more information, the Office of Diversity and Human Rights (DHR) is a welcoming, safe and confidential one-stop shop for information, training and support on issues relating to diversity and human rights on our campus.

All applicants must be eligible to work in Canada specifically at the University of Guelph before applying for an academic work assignment. All successful applicants must perform their work in Ontario and must be able to attend on-campus in-person meetings as required.

Teaching Assistant work assignments are unionized with CUPE 3913 and their terms and conditions of work are covered by the Unit 1 Collective Agreement between the University and CUPE 3913 (email contact: ).

The use of AI to perform job responsibilities must be directed by or approved beforehand in writing by the supervisor or course instructor.