Assistant Professor - Master of Computer Science in Applied AI

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. About The Position Title: Assistant Professor – Applied Artificial Intelligence (MCS – AAI) Location: Niagara Falls, Ontario, Canada (Onsite) Work arrangement: Onsite hybrid, Minimum 2 days per week Reports To: Associate Dean - Applied Artificial Intelligence (MCS – AAI) Expected hiring salary: Minimum salary $ 91,800 Rank and salary are determined through an internal review and approval process The Master of Computer Science in Applied Artificial Intelligence program invites applications for the position, Assistant Professor, Master of Computer Science in Applied Artificial Intelligence. 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 The ideal candidate will have an advanced academic background (PhD) and extensive expertise in the fields of Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a closely related field. The candidate will be responsible to deliver graduate-level courses, mentor students, and contribute to the continued growth and excellence of the program. Key Responsibilities Teaching and Graduate Supervision Teach graduate-level courses within the MCS-AAI program. Develop and deliver innovative, industry-relevant curriculum in applied artificial intelligence. Supervise graduate capstone projects, research projects, and independent studies. Mentor students in academic, professional, and research development. Integrate emerging AI technologies, tools, and methodologies into teaching and learning activities. Support experiential learning opportunities and industry-based projects. Research and Scholarly Activity Establish and maintain an active research agenda in Artificial Intelligence and related disciplines. Publish in high-quality peer-reviewed journals and conferences. Pursue external research funding from government, industry, and funding agencies. Collaborate with faculty, industry partners, and interdisciplinary research teams. Engage graduate students in applied research initiatives. Industry Engagement and Service Build partnerships with industry, government, and community organizations. Support program growth, curriculum enhancement, and accreditation activities. Participate in departmental, faculty, and institutional committees. Contribute to student recruitment, retention, and outreach initiatives. Promote knowledge transfer and innovation through applied AI projects and collaborations. Qualifications And Experience PhD in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or a closely related field. Demonstrated excellence in graduate-level teaching, research, and scholarly activity. Evidence of research productivity through publications, presentations, patents, applied projects, and/or success in securing research funding or industry partnerships. Experience with graduate supervision, mentorship, academic leadership, and/or collaboration in research or professional settings, appropriate to career stage. Strong communication and interpersonal skills, with a commitment to student success and fostering an inclusive learning environment. Preferred Qualifications And Experience Industry experience in artificial intelligence, machine learning, data science, software engineering, or related fields. Experience deploying AI solutions in real-world environments. Knowledge of modern AI frameworks and platforms, including TensorFlow, PyTorch, Hugging Face, LangChain, cloud AI services, and MLOps tools. Experience with online, hybrid, and technology-enhanced learning. Professional certifications in AI, cloud computing, or data analytics. Experience leading interdisciplinary and industry-sponsored research projects. Certified AI Educator (CAIE) credential from PAII is considered an asset 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. Equity, Diversity, Inclusion and Accessibility at UNF The University of Niagara Falls Canada (UNF) is committed to equity, diversity, inclusivity and accessibility within its community and invites applications from all qualified candidates. Racialized persons / persons of color, women, Indigenous People, persons with disabilities, 2SLGBTQIA+ persons, and others who may contribute to the further diversification of ideas are encouraged to apply. 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. All qualified candidates are encouraged to apply; however, Canadian citizens and permanent residents will be given priority. We will accommodate the needs of 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 [email protected] to ensure your accommodation or accessibility needs are supported. Information received relating to accommodation will be maintained confidentially. 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. As part of the recruitment process, selected candidates will be required to successfully complete applicable background and/or credential verifications, or other role-related screenings, in accordance with organizational policy and applicable legislation. We appreciate all applications received; however, only candidates selected for an interview will be contacted. Learn more about the University of Niagara Falls Canada at our website .

The Assistant Professor will deliver graduate-level courses, develop industry-relevant curricula, and supervise graduate research and capstone projects. Additionally, they are expected to maintain an active research agenda, publish in peer-reviewed journals, and build strategic industry partnerships.

Candidates must hold a PhD in Computer Science, Artificial Intelligence, Data Science, or a closely related field. They should demonstrate excellence in graduate-level teaching, research productivity, and experience in mentorship or academic leadership.

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Machine Learning
• Deep Learning
• Generative AI
• Large Language Models
• Natural Language Processing
• Computer Vision
• Reinforcement Learning
• AI Engineering
• MLOps
• Explainable AI
• Agentic AI
• Data Science
• Predictive Analytics
• Robotics
• Human-AI Interaction
• Cloud-Based AI

• Education
• Technology
• Science & Research
• Data & Analytics
• Software

Formation minimale

Maîtrise

Expérience minimale

5+ ans

Postuler avant le

20 août 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Présence au bureau

2 jours par semaine

Niveau d’expérience

Mid-Senior level