Post-Doctoral Research Visit F/M Postdoc position F/M Foundations of resource-efficient large-scale learning

Inria; Lyon; Hybrid; EUR 28,000 - 34,000; Full time

Benefits offered by this job

Partial reimbursement of public oriv?

Job summary

Inria Lyon recherche un post-doctorant pour conduire un programme de recherche ambitieux dans les réseaux profonds épars et l’apprentissage statistique, avec des méthodes numériques avancées. Le candidat doit faire preuve d’autonomie et d’esprit d’équipe, et développer des collaborations avec les groupes à ENS Lyon.

Le poste inclut des ressources expérimentales et des possibilités de télétravail (90 jours/an) ainsi que des déplacements.

Qualifications

• Docteur en mathématiques appliquées, statistiques ou informatique.
• Expérience en apprentissage automatique et traitement du signal.
• Bonnes compétences en programmation et résolution de problèmes.

Responsibilities

• Conduire un programme de recherche lié aux réseaux profonds épars et à l’apprentissage statistique.
• Travailler en collaboration avec l’équipe AllegroAssai et d’autres groupes à ENS Lyon.
• Publier des résultats et présenter l’avancement des travaux.

Skills

Autonomie

Esprit d'équipe

Bonnes compétences en programmation

Education

Docteur en mathématiques appliquées / informatique / statistique

Tools

Python

Matlab

Job description

Post-Doctoral Research Visit F/M Postdoc position F/M Foundations of resource-efficient large-scale learning

Fonction : Post-Doctorant

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.

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.

An internal candidate has been identified, but the position is still open.

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.

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.

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

• 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

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