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methods for assessing generative AI’s compliance to GDPR. The purpose of the position is to build Bayesian metrics for privacy preserving AI(e.g., synthetic data generation, federated learning, and privacy
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is founded by Innovation Found Denmark. Responsibilities: In the project two main approaches are compared. One based on black/gray box machine learning methods and another one on gray/white box data
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opportunity to learn new analysis techniques(e.g., Matlab, Python) if relevant for the task. Write up research results in the form of journal articles. Participate in and co-arrange national and international
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). Training will be provided in all methodologies but prior experience with some techniques is an advantage, and experience in human pain research is a prerequisite. An opportunity to learn new analysis
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Postdoc in statistics to develop Bayesian privacy metrics for synthetic health data (2024-224-05725)
one or more of these additional criteria: Synthetic data generation Machine learning Large health register data GDPR compliance rules Python Linux Valued personal competencies are: Independent and