Sessional Instructor - Master of Computer Science in Applied AI

About the role

**About The University of Niagara Falls Canada**

**Innovation Flows Here.**

Officially opening its doors in 2024, the University of Niagara Falls Canada (UNF) is an innovative and digitally oriented institution that prepares graduates for leadership in the digital world. We believe in delivering programs that provide a direct pathway to meaningful careers in high\-demand industries. UNF is part of the Global University Systems Canada group of institutions and Global University Systems, an international network of higher education institutions.

**Our location**

Our campus is located in historic downtown Niagara Falls. Beyond being Canada’s \#1 travel destination, Niagara Falls is a small vibrant city that offers up a slice of metropolitan living at a different pace. From world\-class dining and entertainment options to luxury shopping and cultural experiences. Our location offers the amenities of a large urban center within a comfortable, liveable community.

**About The Faculty And Department**

The Master of Computer Science in Applied Artificial Intelligence (MCS – AAI) prepares students for careers in AI, machine learning, and data\-driven innovation. The program provides advanced knowledge in machine learning, neural networks, large language models, computational linguistics, data analytics, pattern recognition, and image processing, while emphasizing ethical AI, collaboration, problem\-solving, and real\-world application across a range of industries. Faculty members have the opportunity to work closely with graduate students, industry partners, and research collaborators to advance innovation in artificial intelligence while preparing the next generation of AI professionals and leaders.

The Master of Computer Science in Applied Artificial Intelligence invites applications for sessional instructor positions available for the Fall \[October] academic term.

**Per course rate: $7,200 (paid in installments)**

**Academic Term: Fall 2026 (September 28 – December 13\)**

**Mode of Delivery:** This is a hybrid role. Sessional instructors are required to teach on \-site for a minimum of 2 days per week, though this will depend on their teaching schedule.

We are seeking highly qualified and motivated individuals with a strong background in the following areas to join our diverse faculty team.

* Machine Learning and Deep Learning * Generative Artificial Intelligence and Large Language Models (LLMs) * Natural Language Processing * Computer Vision * Reinforcement Learning * AI Engineering and MLOps * Explainable and Responsible AI * Agentic AI Systems and Autonomous Agents * AI for Cybersecurity * Cloud\-Based AI Solutions * Data Science and Predictive Analytics * Edge AI and Internet of Things (IoT) * Robotics and Intelligent Systems * Human\-AI Interaction

**Key Responsibilities**

* Lecturing \& Teaching: Deliver engaging lectures and instructional content across multiple delivery modes (in\-person, online, or hybrid) to create an inclusive, dynamic learning environment. * Course Materials: Prepare, update, and maintain course materials, including assignments, quizzes, and exams. Ensure materials are accessible and relevant to students’ learning. * Student Engagement: Offer regular office hours to meet with students, address inquiries, and provide academic support. * Assessment \& Grading: Design and grade assignments, tests, and exams in a timely and consistent manner. Provide meaningful feedback to students on their progress. * Curriculum Development: Collaborate on curriculum development to ensure course content is aligned with industry standards and trends. * Technology Integration: Use internal software to manage grades, track progress, and update students on course material.

**Qualifications**

* PhD in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a closely related field. * Prior teaching experience at the post\-secondary level is considered an asset * Knowledge of modern AI frameworks and platforms, including TensorFlow, PyTorch, Hugging Face, LangChain, cloud AI services, and MLOps tools, is preferred. * Experience deploying AI solutions in real\-world environments, is preferred.

**Core Competencies**

* Student\-Centric Approach: Ability to create an inclusive learning environment that promotes student success and engagement. * Effective Communication: Excellent presentation skills with the ability to explain complex topics in an accessible way to students from diverse backgrounds. * Problem Solving: Creative problem\-solving abilities, especially in integrating real\-life case studies and practical examples into the curriculum. * Professionalism: Strong interpersonal skills, diplomacy, and discretion in dealing with colleagues and students. * Time Management: Ability to prioritize tasks and manage multiple responsibilities in a high\-pressure environment.

**Application process**

Interested candidates are invited to submit an application, **using ONE document** that includes a cover letter, resume/curriculum vitae (CV) including evidence of teaching experience and scholarly accomplishments, and teaching portfolio (if applicable), as well as the names of three references. A single PDF document is preferred. Note: file maximum of 5MB per attached upload.

**Use of AI Disclosure**

University of Niagara Falls Canada (UNF), UNF is committed to a fair and transparent recruitment process. While AI tools assist us in identifying and communicating with candidates, applications are reviewed by our dedicated Talent Acquisition team to ensure a thorough evaluation of all candidates.

We value diversity and strive to create an inclusive environment where all individuals have an equal opportunity to succeed. We comply with all relevant laws and regulations in Ontario and adhere to the highest standards of ethical hiring. We are committed to protecting your personal information and ensuring that all data collected during the recruitment process is handled with the highest level of confidentiality.

**Diversity, inclusion, and equity**

UNF is strongly committed to equity, diversity, and inclusivity within its community and especially invites applications from all qualified candidates. Racialized persons / persons of color, women, Indigenous / Aboriginal People of North America, persons with disabilities, 2SLGBTQI\+ persons, and others who may contribute to the further diversification of ideas are encouraged to apply.

We recognize that applicants may have had obligations outside of work that have negatively impacted their record of achievements (e.g., parental, elder care, and/or medical). You are not required to disclose these obligations in the hiring process. If you choose to do so, UNF will ensure that these obligations do not negatively impact the assessment of your qualifications for the position.

All qualified candidates are encouraged to apply; however, Canadian citizens and permanent residents will be given priority.

We will accommodate the needs of the applicants and the Ontario Human Rights Code and the Accessibility for Ontarians with Disabilities Act (AODA) throughout all stages of the selection process, please advise jobs@unfc.ca to ensure your accessibility needs are accommodated through this process. Information received relating to accommodation measures will be addressed confidentially.

We appreciate all applications received; however, only candidates selected for an interview will be contacted.

We are situated on the traditional territory of the Haudenosaunee, Hatiwendaronk and Anishinaabe peoples. We also acknowledge the many other First Nations, Métis, and Inuit peoples who call this region home.

We commit to building relationships based on respect, reciprocity, and reconciliation as we work, learn, and gather on this land. Furthermore, we acknowledge that the Niagara Region is situated on treaty land, and we stand with all Indigenous peoples, past and present, in promoting the wise stewardship of the lands on which we live.

**Learn more about the University of Niagara Falls Canada at our website .**