Postdoctoral Fellow in Computing Science
University of Alberta
Canada

Description

This position is open for an immediate start, is two years in duration, and offers a benefits package found at Postdoctoral Fellows Benefits.

Location - Work primarily takes place at North Campus Edmonton. This role is hybrid with a mix of remote and in-person.

Working at the University of Alberta

The University of Alberta acknowledges that we are located on Treaty 6 territory, and respects the histories, languages and cultures of First Nations, Métis, Inuit and all FirstPeoples of Canada, whose presence continues to enrich our vibrant community.

The University of Alberta is a community of knowledge seekers, change makers and world shapers who lead with purpose each and every day. We are home to over 14,000 faculty and staff, more than 40,000 students and a growing community of 300,000 alumni worldwide.

Your work will have a meaningful influence on a fascinating cross-section of people — from our students and community members, to our renowned researchers and innovators, making discoveries and generating solutions that make the world healthier, safer, stronger and more just. Learn more.

Working for the Department of Computing Science 

Founded in 1964, the Department of Computing Science at the University of Alberta is the oldest and one of the largest computing science departments in Canada. We have an international reputation for contributions in the many fields of computing, both in foundations and applications. The Department currently consists of 51 faculty members, over 300 graduate students, 20 post-doctoral fellows and research associates, over 1300 undergraduate students and 12 administrative staff. Our research partners come from a wide variety of industries and other academic disciplines.

Position 

The Foundations of Robust and Trustworthy Machine Learning (FORT) lab led by Prof Nidhi Hegde has an immediate opening for a postdoctoral researcher. The FORT lab focuses on a fundamental approach to developing robust and trustworthy algorithms for machine learning. This largely applies to notions of privacy and fairness, but also to more general concepts of robustness and stability. Applications range from supervised learning to bandits to language models to image segmentation. The current open position is for a project on Distributionally Robust Optimization as applied to these themes. 

The selected candidate will be hosted in the FORT lab, in the Department of Computing Science at the University of Alberta and the Alberta Machine Intelligence Institute (Amii). Both Amii and the University of Alberta offer numerous opportunities of professional development for postdoctoral researchers to carve their paths, whether in academia or industry.

Duties 

  • Participate in relevant research and direct projects
  • Work with and potentially co-supervise students
  • (Co)-write high impact scientific publications
  • Present your work at top-tier conferences

Minimum Qualifications

  • PhD in computing science or a related area, with a focus on machine learning and statistics
  • Evidence of high-quality research, such as publications in relevant top-tier venues
  • Effective communicator in English, both written and spoken

Preferred Qualifications

  • Expertise in optimization and theory in machine learning is sought
  • Expertise in one or more of game theory, information theory, online learning is an asset

In your cover letter, summarize your past work, link to a representative publication with a description of it, and include a list of three references.

All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority. If suitable Canadian citizens or permanent residents cannot be found, other individuals will be considered.

We thank all applicants for their interest; however, only those individuals selected for an interview will be contacted.

The University of Alberta is committed to an equitable, diverse, and inclusive workforce. We welcome applications from all qualified persons. We encourage women; First Nations, Métis and Inuit persons; members of visible minority groups; persons with disabilities; persons of any sexual orientation or gender identity and expression; and all those who may contribute to the further diversification of ideas and the University to apply.

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