Master Internship - Generative AI for vibration signals

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Le descriptif de l’offre ci-dessous est en Anglais

Type de contrat : Stage

Niveau de diplôme exigé : Bac + 5 ou équivalent

Fonction : Stagiaire de la recherche

Niveau d'expérience souhaité : Jeune diplômé

A propos du centre ou de la direction fonctionnelle

The Inria Saclay-Île-de-France Research Centre was established in 2008. It has developed as part of the Saclay site in partnership with Paris-Saclay University and with the Institut Polytechnique de Paris .

The centre has 40 project teams, 27 of which operate jointly with Paris-Saclay University (15 teams) and the Institut Polytechnique de Paris (12 teams). Its activities occupy over 600 people, scientists and research and innovation support staff, including 44 different nationalities.

The centre also hosts the Institut DATAIA, dedicated to data sciences and their disciplinary and application interfaces.

Contexte et atouts du poste

In the context of a collaborative project between Inria Saclay OPIS and SafranTech, the aim of this internship is to investigate generative AI techniques for non-stationary vibration signals, such as those encountereed in aircraft rotor monitoring.

Subject:  Recent advances in generative artificial intelligence (AI) have shown remarkable success in the image domain, particularly for high-resolution methods such as diffusion models, flow models, and GANs [1,2]. In this internship, we investigate AI generative techniques to handle non-stationary signals, aiming to develop an AI model for super-resolution of time-frequency (TF) representations. 

During this internship, the student will conduct a literature review on TF super-resolution [3], including optimization-based, discriminative, and generative methods. They will implement a AI-based TF super-resolution algorithm, evaluate it on synthetic datasets, and explore potential real-world datasets for application. 

The research conducted during this project has the potential to result in a publication in leading conferences on artificial intelligence or signal processing.

[1] Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David
Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. Gener-
ative adversarial networks, 2014.

[2] Ségolène Martin, Anne Gagneux, Paul Hagemann, and Gabriele Steidl.
Pnp-flow: Plug-and-play image restoration with flow matching, 2025.

[3] Vasile V Moca, Harald Barzan, Adriana Nagy-Dabacan, and Raul C
Mures. Time-frequency super-resolution with superlets. Nature com-
munications, 12(1):337, 2021.

Mission confiée

Missions: Literature review ; Implementation ; Evaluation on public datasets

Environment: The intern will be supervised by Emilie Chouzenoux (Head of OPIS team, Inria Saclay) and Imed Moussa (PhD student, OPIS-SafranTech). The intern student will join the Inria Saclay team OPIS (https://opis-inria.eu/). He/she will be located in the Centre de la Vision Numérique, in CentraleSupélec campus, Saclay, France. He/she will enjoy an international and creative environment where research seminars and reading groups take place very often. Informatic material expenses will be covered within the limits of the scale in force.

Organization: The proposed offer is dedicated to internship of Master 2 students. The starting/end dates
are flexible, with a minimum duration of 5 months.

Principales activités

Main activities :

Programming in Python environment

Bibliographical study

Deep learning architecture design

Scientific meetings

Deep learning training/testing

Writing of scientific reports

Compétences

Languages : The candidate must be fluent in english and/or french languages.

Avantages

  • Canteen and cafeteria;
  • Sports equipment;
  • Transport reimbursement

 

Rémunération

Gratification