Post-Doctoral Research Visit F/M Postdoctoral research position offer

_Le descriptif de l’offre ci-dessous est en Anglais_ TYPE DE CONTRAT : CDD CONTRAT RENOUVELABLE : Oui NIVEAU DE DIPLÔME EXIGÉ : Thèse ou équivalent FONCTION : Post-Doctorant A PROPOS DU CENTRE OU DE LA DIRECTION FONCTIONNELLE The Inria Sophia Antipolis - Méditerranée center counts 34 research teams as well as 7 support departments. The center's staff (about 500 people including 320 Inria employees) is made up of scientists of different nationalities (250 foreigners of 50 nationalities), engineers, technicians and administrative staff. 1/3 of the staff are civil servants, the others are contractual agents. The majority of the center’s research teams are located in Sophia Antipolis and Nice in the Alpes-Maritimes. Four teams are based in Montpellier and two teams are hosted in Bologna in Italy and Athens. The Center is a founding member of Université Côte d'Azur and partner of the I-site MUSE supported by the University of Montpellier. CONTEXTE ET ATOUTS DU POSTE With the launch of a new partnership between Inria and Fujitsu, we seek to hire an excellent candidate for a postdoctoral research position specialized in data science and machine learning. The successful candidate will be primarily based at Inria Sophia-Antipolis in France, in the DataShape team. Since part of the team is also located in Orsay, some trips to meet people from Inria Saclay may be needed. The successful candidate will potentially spend some time in Fujitsu’s offices in Tokyo, Japan as well. MISSION CONFIÉE Your goal will be to develop mathematical frameworks and practical setups for applying TDA methods, descriptors and features in the context of large-scale data sets processed with non-convex optimization and deep learning techniques (such as, e.g., deep clustering, metric learning, GANs, autoencoders, reinforcement learning, etc.). This includes, in particular, the mathematical analysis and empirical study of applicability, scalability, theoretical properties and performances of TDA-based methods over traditional approaches on a wide range of data sets. PRINCIPALES ACTIVITÉS Development of deep generative models for persistent homology and other TDA descriptors Theoretical framework for smooth optimization with TDA-based losses Mathematical and statistical analysis of TDA-based descriptors in machine learning Development of TDA-based regularization and robustness quantification methods for deep learning COMPÉTENCES Academic level: PhD Language: English (fluent), French (optional) Libraries: Scikit-Learn, PyTorch/TensorFlow, Gudhi (optional) 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 (after 6 months of employment) 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 Gross Salary: 2653 € per month