Post-Doctoral Research Visit F/M Distributed Machine Learning at the Network Edge

Post-Doctoral Research Visit F/M Distributed Machine Learning at the Network Edge

Fonction : Post-Doctorant

Inria is the French National Institute for Research in Digital Science, of which the Inria Côte d'Azur University Center is a part. With strong expertise in computer science and applied mathematics, the research projects of the Inria Côte d'Azur University Center cover all aspects of digital science and technology and generate innovation. Based mainly in Sophia Antipolis, but also in Nice and Montpellier, it brings together 47 research teams and nine support services. It is active in the fields of artificial intelligence, data science, IT system security, robotics, network engineering, natural risk prevention, ecological transition, digital biology, computational neuroscience, health data, and more. The Inria Center at Université Côte d'Azur is a major player in terms of scientific excellence, thanks to the results it has achieved and its collaborations at both European and international level.

The position is in the framework of dAIEDGE---A network of excellence for distributed, trustworthy, efficient and scalable AI at the Edge---funded by the European Union. The vision of the dAIEDGE Network of Excellence is to strengthen and support the development of the dynamic European edge AI ecosystem under the umbrella of the European AI Lighthouse and to sustain the advanced research and innovation of distributed AI at the edge as essential digital, enabling, and emerging technology in an extensive range of industrial sectors.

We are looking for a postdoc candidate who could join our team to work on one or more of the following topics:

• Distributed Inference
• Online Learning Algorithms with Regret Guarantees
• Distributed/Federated Learning
• Machine Learning Privacy

We expect the postdoc to actively participate to the activities of the EU project dAIEDGE (e.g., attending meetings, coordinating Inria contribution to deliverables). The postdoc will also have the opportunity to collaborate with PhD students working on the topics listed above.

Candidates must hold a Ph.D. in Applied Mathematics, Computer Science or a closely related discipline. Candidates must also show evidence of research productivity (e.g. papers, patents, presentations, etc.) at the highest level.

We prefer candidates who have strong mathematical background (on optimization, statistical learning or privacy) and in general are keen on using mathematics to model real problems and get insights. The candidate should also be knowledgeable on machine learning and have good programming skills. Previous experiences with PyTorch or TensorFlow is a plus.

Avantages

• 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
• Contribution to mutual insurance (subject to conditions)