Temporary scientific engineer
Il y a 7 mois
Contexte et atouts du poste
This engineer position will be supported by the CAPS'UL project. The position will be based in the MAGNET team in Lille, in very close collaboration with the Lille Hospital.
The CAPS'UL project objective is to promote digital health culture for current and future healthcare professionals. Part of the project concerns the design of a high-performance tool for practical situations, enabling concrete and effective collaboration between the various training, socio-economic and medico-social players in the implementation of training courses. It will provide a credible immersive environment (real software and simulated healthcare data) and teaching scenarios for the entire teaching community.
The INRIA MAGNET team (and hence the recruited collaborators) will contribute to this project by researching machine learning algorithms for synthetic data generation with privacy constraints and dedicated to training.
Mission confiée
The recruited engineer will collaborate with colleagues in the MAGNET team and the CAPS'UL project consortium. In particular, the work will contribute to build a platform for synthetic (longitudinal) data generation together with a toolbox for privacy auditing. The main originality lies in the definition of data utility as it should reflect the variety of situations that can help professionals in a training context.
All developed software will be open-source.
Principales activités
The principal activities will be in two steps.
First period Select and gather state of the art implementations of machine learning methods for synthetic data generationExtract and prepare health data for training machine modelsGenerate synthetic data and evaluate privacy with state of the art attacksTest algorithms and run experiments Second period Design and prototyping of key algorithmsCreate appropriate tests and documentationIntegrate such implementations in the CAPS'UL platformTest algorithms and run experiments
Compétences
Strong background in Computer Science Strong programming skills in Python Background in privacy and machine learning Prior experience in the health domain will be an asset
Avantages
Subsidized meals Partial reimbursement of public transport costs Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.) Possibility of teleworking and flexible organization of working hours Professional equipment available (videoconferencing, loan of computer equipment, etc.) Social, cultural and sports events and activities Access to vocational training Social security coverage
Rémunération
According to profile
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