Apriora Identifies Top Candidates for Professors at The University of Alberta

The Customer‍

The University of Alberta is one of Canada’s top research institutions, home to over 40,000 students and a diverse range of academic programs. When hiring for specialized roles, departments like Civil and Environmental Engineering require a rigorous process to ensure candidates meet highly technical and interdisciplinary criteria. In one recent hiring cycle, the team turned to Alex to help streamline their evaluation process and identify top candidates faster.

Alex even identified two amazing candidates that our professors did not initially shortlist because their CVs were not well aligned with the advertisement. We ended up moving forward with both.
– Samer Adeeb, Chair of Civil and Environmental Engineering, University of Alberta

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The Challenge‍

Hiring for a niche Ph.D. position, the department faced several challenges:

1. Limited time and bandwidth: Professors had to manually review and evaluate 30+ applications, each requiring nuanced academic and technical judgment.
   
2. Need for interdisciplinary fit: The role required deep expertise in both civil engineering and dentistry, an uncommon combination not easily vetted via resumes alone.
   
3. Risk of overlooking strong candidates: Traditional resume and cover letter reviews sometimes led to strong applicants being missed due to formatting or lack of detail.

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The Solution‍

To test Alex’s capabilities, the department conducted a side-by-side experiment, comparing results from their traditional manual screening process with Alex’s AI-led process.

Professors provided Alex with the job description, which was used to generate a custom interview and scoring rubric. Alex then interviewed all applicants, evaluated their responses against the rubric, and produced a ranked shortlist.

Key benefits included:

1. Aligned evaluations: Three of the four candidates manually selected by professors were also top-ranked by Alex.
2. Added value: Alex surfaced two additional candidates who were initially overlooked but ultimately moved forward.
3. Saved time: The AI handled all outreach, interview scheduling, and evaluation, freeing up hours of faculty time.
   
   

We were impressed by how closely Alex’s results matched ours, and even more so by the strong candidates we would have missed without her.
– Samer Adeeb

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The Results‍

With Alex in the process, the University of Alberta accelerated its screening workflow while preserving academic rigor.

1. 3 of the 4 manually shortlisted candidates were also top-ranked by Alex, validating the AI’s precision.
2. 2 overlooked candidates identified by Alex were added to the final shortlist after strong interviews.
3. All 30 candidates were interviewed, scored, and ranked in a matter of days, not weeks.
   
   

What’s Next‍

Encouraged by the results, the University of Alberta is exploring how Alex can be used more broadly across departments to save time, reduce bias, and increase hiring accuracy for technical and academic roles. With Alex, they can ensure a consistent, data-driven evaluation process that doesn’t compromise on quality.

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