phd position f/m privacy-preserving methods for medical research
Inria
Universidad Estatal, Examinar oportunidades similares
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Universidad Estatal, Examinar oportunidades similares
This PhD student position will be supported by the ANR-PMR project on Privacy-preserving methods for Medical Research. This project is a collaboration between the MAGNET team (INRIA-Lille, https://team.inria.fr/magnet/ ), the MYRIAD team (INSA-Lyon) and PRIVATICS (INRIA-Lyon, INSA-Lyon).
While this position will be in the MAGNET team in Lille, it will hence be in a collaboration with the other teams of the PMR project and involve the appropriate travel and/or meetings. Moreover, for the validation of the research, we will collaborate with one or more hospitals, e.g., the INCLUDE team at CHU-Lille.
Given the growing awareness of privacy risks of data processing, there is an increasing interest in privacy-preserving learning. However, shortcomings in the state of the art limit the applicability of the privacy-preserving learning paradigm. First, most approaches assume too optimistically a honest-but-curious setting. Second, most approaches consider one learning task in isolation, not accounting for the context where querying is a recurring activity. We will investigate new algorithms and models that address these shortcomings. Among others, (i) our algorithms will combine privacy-preserving properties of differential privacy with security offered by cryptography and (ii) based on models of information flows in integrated data handling processes, we will build more refined models analyzing the implications of repeated querying. We will demonstrate the utility of our new theory and algorithms by proposing strategies to realistically apply them in significant real-world problems illustrated through use cases in the medical domain.
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