Doctoral Position - Acoustic

Universities and Institutes of France
November 10, 2022
Contact:N/A
Offerd Salary:Negotiation
Location:N/A
Working address:N/A
Contract Type:Temporary
Working Time:Full time
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Job Ref.:N/A
  • Organisation/Company: Le Mans University
  • Research Field: Ethics in health sciences › Other
  • Researcher Profile: First Stage Researcher (R1)
  • Application Deadline: 10/11/2022 12:00 - Europe/Brussels
  • Location: France › LE MANS
  • Type Of Contract: Temporary
  • Job Status: Full-time
  • Hours Per Week: 35
  • Offer Starting Date: 01/12/2022
  • PhD thesis proposal

    Title of the thesis : Artificial Intelligence (AI) classification of acoustic and eddy current

    signals for non-destructive testing of materials and structures: from sensor to data processing

    Context and objectives :

    Non Destructive Testing (NDT) relies on the exploitation of signals from physical

    measurements to ensure the integrity and health of materials and structures. Different wavematter

    interactions (active, passive, acoustic, electromagnetic, thermal,...) allow to detect and

    size defects through an analysis of the measured signals. These inspection methods rely on the

    interpretation of the test results by a qualified operator. The inspection of large structures in

    various fields (Nuclear, Aeronautics, Civil Engineering,...) as well as the taking into account of

    the high rate of inspection constitute an important point of improvement of controls. In this

    regard, AI is an excellent tool to automate the analysis and classification of defects, as well as

    to identify the healthy areas of areas likely to contain defects. The advantages of AI algorithms

    in physical measurement in terms of accuracy and sensitivity for good decision making are

    widely recognized in different fields. On the other hand, the relative opacity of these algorithms

    and their lack of explicability is a hindrance to their acceptability and their full development in

    the NDT community. The handling of these tools and their relation with the observed physical

    phenomena would allow a better understanding of the algorithms in play and the definition of

    relevant indicators allowing to optimize the precision of the control in order to gain in time and

    in efficiency while keeping a high level of requirement as for the safety of materials and

    structures.

    The objective of the thesis is the development of tools for the analysis and automatic

    classification of acoustic and electromagnetic signals, in particular eddy currents, in a Python

    environment. The signals will be analyzed and classified according to artificial intelligence

    models. Particular attention will be paid to the explicability of the developed algorithms and to

    the physical interpretation of their functioning. The databases that will be exploited will come

    from :

    - Anonymized databases available in the framework of the France Relance Project "AUTEND”

    - Existing data bases / realized in laboratory from mechanical tests on several classes of

    materials (Composites, polymers, metals, concretes,...)

    - Databases of acoustic signals and passive tomography where the PhD student will develop the

    control chain from the sensor to the data analysis by optimizing the choice of sensors,

    instrumentation and data processing.

    The beginning of the thesis will take place as soon as possible, at the latest on december 1st and

    this for a duration of 3 years within the framework of a doctoral contract financed by the France

    Relance project "AUTEND" coordinated by the company Omexom, subsidiary of Vinci-

    Energie.

    General presentation of the host laboratory:

    The thesis work will take place mainly at the Laboratoire d'Acoustique de l'Université du Mans

    (LAUM), a joint research unit UMR 6613 Le Mans University - CNRS. The staff of the

    laboratory is about 160 persons: professors, researchers, BIATSS/ITA (engineers and

    technicians), PhD students, post-doctoral fellows, associated researchers". The activities of the

    laboratory are focused on the acoustics of the audible, vibration of structures and nondestructive

    testing and acoustic health control (https:// laum.univ- lemans.fr/fr/index.html).

    General presentation of the project partners:

    This thesis is part of the AUTEND project which is led by three partners:

    - The Acoustics Laboratory of the University of Le Mans (LAUM), which contributes to the

    optimization, and to the implementation of the analyses and the data processing within the

    framework of the project;

    - OMEXOM NDT Engineering & Services, a subsidiary of VINCI Energies, which develops,

    qualifies and implements control processes for critical components of nuclear power plants.

    OMEXOM is the pilot of the project;

    - ALEIA, a French startup specialized in AI, designs and develops the artificial intelligence

    platform required for the project and industrializes the business application;

    Supervision:

    The supervision of the thesis will be provided by Rachid EL GUERJOUMA teacher

    researcher at LAUM and Charfeddine MECHRI Teacher-Researcher at LAUM and Research

    Engineer at CTTM (Center for Technology Transfer of Le Mans)

    T o apply, you must consult the job description available on this link :

    https: // www. univ-lemans.fr/fr/universite/s-engager-a-nos-cotes/nous- recr...

    Web site for additional job details

    https: // www. univ-lemans.fr/fr/universite/s-engager-a-nos-cotes/nous- recrutons...

    https: // laum.univ-lemans.fr/fr/index.html

    Offer Requirements
  • REQUIRED EDUCATION LEVEL
  • Ethics in health sciences: Master Degree or equivalent

    Skills/Qualifications
    The doctoral student must hold a Master's degree or equivalent. 
    The monthly salary is 1975 € gross.
    
    Contact Information
  • Organisation/Company: Le Mans University
  • Department: LAUM
  • Organisation Type: Public Research Institution
  • Website: https: // laum.univ-lemans.fr/fr/index.html
  • E-Mail: rachid.elguerjouma@univ-lemans.fr charfeddine.mechri@univ- lemans.fr
  • Country: France
  • City: Le Mans
  • Street: Av Olivier Messiaen
  • Phone: (+33)243833937
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