PhD Research Fellow in fairness in artificial intelligence (ref 307994)

University of Oslo; Norway; On-site; NOK 520,000 - 600,000; Full time

Job summary

The University of Oslo invites applications for a PhD Research Fellow position in fairness in artificial intelligence, within the Department of Informatics, in the Scientific Computing and Machine Learning (SCML) group.

The successful candidate will work on formal definitions, measurements and reconciliation of different notions of fairness in AI systems, supervised by an associate professor.

Qualifications

• PhD Research Fellow position in fairness in AI at the Department of Informatics, University of Oslo.
• Affiliation with the Scientific Computing and Machine Learning (SCML) group.

Responsibilities

• Investigate how to formally define, measure and reconcile notions of fairness in AI systems.
• Explore theoretical relationships between different notions of fairness and methods to reconcile them.

Skills

Fairness in AI

Machine Learning

Job description

Organisation/Company University of Oslo Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 2 Oct 2026 - 23:00 (Europe/Oslo) Country Norway Type of Contract Temporary Job Status Full-time Hours Per Week 37.5 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No

Offer Description

We invite applications for a PhD Research Fellow position in fairness in artificial intelligence, available at the Department of Informatics, in the Scientific Computing and Machine Learning (SCML) research group.

The PhD fellow will be affiliated with the Scientific Computing and Machine Learning (SCML) research group at the Department of Informatics and supervised by associate professor Anne-Marie George.

We are looking for a motivated and academically strong candidate to work on a project within fairness in artificial intelligence and machine learning. The candidate will investigate how to formally define, measure and reconcile different, at times conflicting, notions of fairness in AI systems, as well as the theoretical relationships between them.