Post-Doctoral Research Visit F - M Postdoc Position F - M Foundations Of Resource-Efficient Large-Scale Learning H/F - INRIA

A propos d'Inria

Inria, l'institut national de recherche dans les sciences et technologies du numérique, est en appui de l'État pour les stratégies nationales de recherche et d'innovation du numérique en tant qu'Agence de programmes. Inria mène plus de 300 projets de recherche et d'innovation avec ses 3500 scientifiques, ingénieurs et personnels d'appui, en partenariat avec les universités et l'écosystème numérique (entreprises, entrepreneurs, acteurs publics). Ensemble, nous explorons des domaines clés comme l'intelligence artificielle, la cybersécurité, l'informatique quantique, le Cloud, la transformation numérique de la santé, les jumeaux numériques ou encore les technologies numériques pour la défense. Nous construisons des solutions concrètes telles que des logiciels, des startups technologiques, des partenariats avec les entreprises du tissu national et des formations de pointe. Notre objectif : l'impact scientifique, technologique et industriel au service de la souveraineté numérique de la France.

Post-Doctoral Research Visit F/M Postdoc position F/M Foundations of resource-efficient large-scale learning
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 research centre in Lyon is the 9th Inria research centre, formally created in January 2022. It brings together approximately 300people in 17 research teams and research support services.

Its staff are distributed in Villeurbanne, Lyon Gerland, and Saint-Etienne.

The Lyon centre is active in the fields of software, distributed and high-performance computing, embedded systems, quantum computing and privacy in the digital world, but also in digital health and computational biology.

Contexte et atouts du poste

Within the framework of a partnership

Founded in 1880, the Ecole Normale Supérieure de Lyon (www.ens-lyon.fr) is one the most prestigious Grand Écoles in France with students selected from the top 5% among all students in the country and among the best students from abroad. The mission of the university is training national and international future professors, researchers, senior civil servants as well as business and political leaders, and to advance research in several disciplines ranging from humanity to natural sciences.

Established in 1967, Inria (www.inria.fr) is the only public research body in France fully dedicated to computational sciences. Combining computer sciences with mathematics, Inria's 3,500 researchers strive to invent the digital technologies of the future. Educated at leading international universities, they creatively integrate basic research with applied research and dedicate themselves to solving real problems, collaborating with the main players in public and private research in France and abroad and transferring the fruits of their work to innovative companies.

Mission confiée

Solid algorithmic and mathematical foundations are essential to endow machine learning systems with guaranteed utility, resource-efficiency and trustworthiness. A particular challenge is to control the tradeoffs between performance and computational footprint to exploit massive data streams.

The recruited postdoc will conduct a vigorous research program within the scope of the project, and is expected to show independence and team working attitude at the same time.

The successful candidate, which can come from different areas (applied mathematics and statistics, signal processing, machine learning, information theory, computer science) is expected to bring expertise to the AllegroAssai task force and will be encouraged to develop collaborations with other groups at ENS de Lyon.

The position is endowed with travel, computing, and experimental resources.

Sample research topics include: Expressivity and Robustness of Sparse Deep Networks; Provable Algorithms for Sparse Deep Learning; Random Sketches for Efficient Manifold & Graph-based Learning.

Principales activités

Sample research topics include: Expressivity and Robustness of Sparse Deep Networks; Provable Algorithms for Sparse Deep Learning; Random Sketches for Efficient Manifold & Graph-based Learning.

Compétences

Candidates should hold a Ph.D., and will either be applied mathematicians with interest for statistical signal processing, and good programming skills, or originate from signal processing / computer science with solid background in applied mathematics and statistics. Previous experience in sparse signal representations or statistical machine learning is preferred, but experience in related areas is suitable.

Avantages

- Subsidizedmeals
- 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 (90 days / year) and flexible organization of working hours Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage under conditions

Rémunération

Gross salary:2788 € gross salary / month (social security included, income tax excluded).

• Anglais
• Machine learning