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

Inria, the French national research institute for the digital sciences; France; Hybrid; EUR 28,000 - 34,000; Full time

Benefits offered by this job

Remboursement partiel des frais de 运输

Congés: 7 semaines + RTT

Possibilité de télétravail (90 jours /

Job summary

Inria, the French national research institute for the digital sciences, Lyon is seeking a postdoctoral researcher. You will conduct a vigorous research program within the AllegroAssai project, demonstrating independence while collaborating with ENS de Lyon and Inria teams.

Candidates should hold a Ph.D. and may come from applied mathematics and statistics, signal processing, machine learning, information theory or computer science.

Qualifications

• Docteur en domaine pertinent exigé (mathématiques appliquées, statistiques, traitement du signal, apprentissage automatique, théorie de l’information ou informatique).
• Excellentes compétences en programmation souhaitées.

Responsibilities

• Conduire un programme de recherche ambitieux dans le cadre du projet AllegroAssai.
• Montrer autonomie tout en travaillant en équipe et en collaboration avec l’ENS de Lyon et Inria.
• Contribuer à des activités de diffusion et à des collaborations intergroups.

Skills

Programming skills

Education

Ph.D. in a relevant field

Job description

Inria, the French national research institute for the digital sciences

Organisation/Company Inria, the French national research institute for the digital sciences Research Field Computer science Researcher Profile Recognised Researcher (R2) Application Deadline 13 Nov 2026 - 00:00 (UTC) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 38.5 Offer Starting Date 1 Dec 2026 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Reference Number 2026-10611 Is the Job related to staff position within a Research Infrastructure? No

Offer Description

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.

Languages FRENCH Level Basic

Languages ENGLISH Level Good

Additional Information

• 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).

Selection process