PhD Research Fellow in Machine Learning and Statistics

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.

For more information and how to apply: https://www.jobbnorge.no/en/available-jobs/job/308211/phd-research-fellow-in-machine-learning-and-statistics

Requirements

• Research Field: Computer science
• Education Level: Master Degree or equivalent

Work Location(s)

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

Contact

• City: Oslo
• Website: https://www.integreat.no/
• Street: PO box 1072 Blindern
• Postal Code: NO-0316
• E-Mail: ingrihaf@math.uio.no
• ali@ifi.uio.no