Research Engineer in AI

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Type de contrat : Fixed-term contract

Contrat renouvelable : Oui

Niveau de diplôme exigé : Graduate degree or equivalent

Fonction : Temporary scientific engineer

Niveau d'expérience souhaité : Recently graduated

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 , 32 of which operate jointly with Paris-Saclay University and the Institut Polytechnique de Paris; Its activities occupy over 600 people, scientists and research and innovation support staff, including 44 different nationalities.

Contexte et atouts du poste

The engineer will be part of the OPIS project team, reporting to team leader Emilie Chouzenoux.

The project will be carried out in collaboration with E. Chouzenoux and J.-C. Pesquet (OPIS), C. Lefort, CNRS research scientist at XLIM, Limoges, and the CHU of Limoges.

This is a one-year contract, renewable once.

Mission confiée

CARS Microscopy (Coherent Anti-Stokes Raman Scattering) is an advanced nonlinear optical imaging technique that enables the acquisition of vibrational information from biomedical samples without labeling (label-free). The use of broadband laser sources known as "supercontinuum" has been introduced to explore all the energy transitions of the sample. With spectral detection of the instrument, M-CARS imaging becomes hyperspectral (HM-CARS). Each pixel in the image contains a spectrum of 1024 points, depending on the composition of the target substances.

Through this original approach, the researchers recently demonstrated that the “silent zone” of an HM-CARS spectrum actually provides discriminating information about the sample. This technique remains unexplored in the biomedical field. The current method of data processing is tedious and can encounter a number of practical difficulties.

The main objective of this work is to exploit the database through the development of fast, accurate and automatized AI strategies to identify discriminating information related to muscular diseases.

Principales activités

  • Understand the image processing problem
  • Analyze the database
  • Deploy a supervised AI approach to solve the problem
  • Write scientific reports
  • Participate in scientific meetings with collaborators

Compétences

  • Proficiency in the Python programming language and the PyTorch or TensorFlow environment is required.
  • Experience in machine learning / neural networks is strongly recommended.

Avantages

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

Rémunération

Regarding professional experience