PhD Research Fellow in Machine Learning and Statistics (ref 308211)

University of Oslo; Norway; On-site; NOK 520,000 - 640,000; Full time

Job summary

University of Oslo invites applications for a doctoral research fellow in Machine Learning and Statistics. The position offers integration with Integreat and a collaborative, interdisciplinary research environment focused on mentoring and career development.

The project develops deep learning based synthetic data generators emphasizing privacy and fairness, at the intersection of ML, statistics and ethics, affiliated with the Statistics and Data Science group in the Department of Mathematics,

Qualifications

• Strong background in machine learning and statistics.
• Interest in privacy-preserving synthetic data and fairness.
• Willingness to collaborate across disciplines.

Responsibilities

• Contribute to development of deep learning based synthetic data generators.
• Assess privacy, fairness and utility of proposed methods.
• Engage in mentoring and career development within the group.

Skills

Machine Learning

Statistics

Privacy

Deep Learning

Ethics

Education

PhD in ML/Statistics

Job description

Organisation/Company University of Oslo Research Field Computer science Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 16 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

Integreat - the Norwegian Centre for Knowledge-driven Machine Learning at the University of Oslo invites applications for a doctoral research fellow in Machine Learning and Statistics. We seek a motivated researcher, who values collaboration, inclusivity, and impact, and who would like to contribute to a supportive, interdisciplinary research environment with strong focus on mentoring and career development.

We welcome applicants with a strong background in machine learning and statistics, who are eager to contribute to cutting-edge methods for generating private and fair synthetic data with good utility. This project involves development of deep learning based synthetic data generators that obtain both good utility and protection of privacy, through tailored model approximation, as well as new measures of privacy and fairness to be used for assessing properties of synthetic generators, or in loss functions for training them. Further, the potentials and limitations of the developed approaches should be critically assessed regarding their implications for fairness, privacy, and utility. This project is at the intersection of machine learning, statistics and ethics.

This position is affiliated with the research group research group in Statistics and Data Science at the Department of Mathematics at University of Oslo, in close collaboration with the machine learning group at the Department of Informatics.

Number of offers available 1 Company/Institute Norwegian Centre for Knowledge-driven Machine Learning Country Norway Geofield