Software engineer on private and decentralized machine learning

A propos du centre ou de la direction fonctionnelleThe Inria University of Lille centre, created in 2008, employs 360 people including 305 scientists in 15 research teams. Recognised for its strong involvement in the socio-economic development of the Hauts-De-France region, the Inria University of Lille centre pursues a close relationship with large companies and SMEs. By promoting synergies between researchers and industrialists, Inria participates in the transfer of skills and expertise in digital technologies and provides access to the best European and international research for the benefit of innovation and companies, particularly in the region.For more than 10 years, the Inria University of Lille centre has been located at the heart of Lille's university and scientific ecosystem, as well as at the heart of Frenchtech, with a technology showroom based on Avenue de Bretagne in Lille, on the EuraTechnologies site of economic excellence dedicated to information and communication technologies (ICT)Contexte et atouts du posteThe position will be supported by FedMalin, a collaborative project on Federated Learning between 11 teams at INRIA. The project addresses FL challenges when deployed over the internet (privacy, heterogeneity, energy, fairness, ...) and has medicine as a main targeted application domain.FedMalin develops several software tools, including the open source library DecLearn (https : / / gitlab.inria.fr / magnet / declearn / declearn2) for private and decentralized / federated machine learning and data analysis. The hired engineer will contribute to the ongoing development of DecLearn, expanding its capabilities with new algorithms and enhanced functionalities.The activities will include interactions with the members of the project, the Magnet and Premedical teams (researchers and engineers). We also expect to conduct multi-centric medical studies across several hospitals. The activities can also include travel, e.g., to conferences to demonstrate the developed library and to contribute to the community building effort.Mission confiéeConsolidate and extend the existing library for decentralized and privacy-preserving machine learning developed in the projectDeploy the library in real-world conditions and experiment on synthetic and (benchmark) medical data, analyzing the benefits and the costs compared to a centralized approach.Publish open source code and integrate in existing librariesPublish scientific results in medical and computer science conferencesThe Declearn project is available at https : / / gitlab.inria.fr / magnet / declearn / declearn2Principales activitésImplement federated and privacy-preserving algorithms for machine learningExperiment with medical partners on multicentric medical studiesEvaluation of resultsReporting, disseminating and presenting resultsCompétencesProgramming skills in Python, including object oriented programming, unit testing, documentation writing, deployment tools, asynchronous programming and networking.Good understanding of scientific papers on machine learning.Interest for machine learning and medical applications.Good communication skills; communication and animation of software development communities, git workflowAvantagesSubsidized mealsPartial reimbursement of public transport costsLeave : 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 hoursProfessional equipment available (videoconferencing, loan of computer equipment, etc.)Social, cultural and sports events and activitiesAccess to vocational trainingSocial security coverageRémunérationAccording to profile #J-18808-Ljbffr