Tenure-Track Position in AI/ML/DL Theory

The Department of Computing Science at the University of Alberta invites applications for a tenure-track position (Assistant or, in exceptional cases, Associate Professor level), starting as early as July 1st, 2025 in the area of Artificial Intelligence/Machine Learning (ML)/Deep Learning (DL) Theory. Additional strength in general CS Theory (e.g., Data Structures & Algorithm; Streaming, Sketching, and Big Data Algorithms; Computational Complexity; Discrete Optimization; etc.) will be an asset. Other areas of expertise in AI, ML, and DL may be considered.

The successful candidates must hold a Ph.D. (or equivalent) degree, whose primary focus is in Artificial Intelligence, Machine Learning, or Software Engineering, by the appointment date. They are expected to have demonstrated research potential strong enough for a promising nomination as Canada CIFAR AI Chair, evidenced by publications in top venues (conferences or journals) within the area of AI/ML/DL Theory. They should also have strong communication skills and demonstrated commitment to highly effective graduate and undergraduate teaching. They will be expected to establish their own funded research programs, supervise graduate students, and teach graduate and undergraduate courses. Strong potential for productive interactions with other researchers in the Department and in other disciplines at the University of Alberta will be considered an asset.  

The successful candidate will be nominated for a Canada CIFAR Artificial Intelligence (CCAI) Chair by the Alberta Machine Intelligence Institute (Amii). The CCAI Chair includes research funding for at least five years. This position is part of a University of Alberta cluster hire in the intersection of Machine Learning and other areas, including areas of research strength that include Health, Energy, and Indigenous Initiatives in health and humanities, among others.  The successful candidate will also become an Amii Fellow, joining a highly collegial institute of world-class Artificial Intelligence and Machine Learning researchers, have access to Amii internal funding resources, administrative support, and a highly collaborative environment.

The Department of Computing Science is one of the largest and oldest computing science departments in Canada. The Department has 55 tenured/tenure-track faculty members and 7 academic teaching staff who are recognized for their excellence in research and teaching at the international, national, and university level. The Department’s student population includes approximately 567 graduate students, 1,193 undergraduate honors and specialization students and over 1,370 undergraduate majors/minors. Approximately 6,116 undergraduate students are enrolled in Computing Science courses each term. The University of Alberta is home to over 44,000 students from 156 countries (divided roughly as 80% undergraduate and 20% graduate students) and 600 postdoctoral fellows.  

Amii is one of three institutes named in the Pan-Canadian AI Strategy and consists of more than 35 artificial intelligence and machine learning researchers at the U of A, as well as CCAI Chairs at post-secondary institutions across Western Canada. The University of Alberta is world-renowned for its strength in AI and ML, which the University has identified as one of three priority areas of global research prominence (University Strategic Plan). The AI cohort that includes this position will bring together and foster the next generation of scientists leading the development of machine learning for societal benefit, fulfilling Amii’s mandate of AI for good and for all.

The University of Alberta is committed to Equity, Diversity and Inclusivity (Strategic Plan for EDI) and to reconciliation (Indigenous Strategic Plan). The computing science department is committed to advancing equity, diversity and inclusion, and has an active EDI committee. We welcome applications from all qualified persons, including those with non-traditional career paths. Applicants are also encouraged to discuss, in their submitted statements (see below), how they will contribute to expanding the diversity of our campus with their research, supervision, teaching, and public outreach.

Applicants are asked to submit the following documents: