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  • Research

    The fundamental principle of IRCAM is to encourage productive interaction among scientific research, technological developments, and contemporary music production. Since its establishment in 1977, this initiative has provided the foundation for the institute’s activities. One of the major issues is the importance of contributing to the renewal of musical expression through science and technology. Conversely, sp…

    • Research Topics
    • The STMS Lab
    • Research Teams
    • Sound Systems and Signals: Audio/Acoustics, InstruMents
    • Acoustic and Cognitive Spaces
    • Perception and Sound Design
    • Sound Analysis-Synthesis
    • Sound Music Movement Interaction
    • Musical Representations
    • Analysis of Musical Practices
    • Projects
    • Sound Workshop
    • The Musical Body
    • Creative Dynamics
    • Musique/Sciences Collection
  • Creation

    IRCAM is an internationally recognized research center dedicated to creating new technologies for music. The institute offers a unique experimental environment where composers strive to enlarge their musical experience through the concepts expressed in new technologies.

    • Composers & Artists in Studio
    • In Ex Machina
    • Jazz Ex Machina
    • Improvise cum machina 1/2
    • Improvise cum machina 2/2
    • Like Sound, Like Flesh
    • Silent Talks
    • Music-Fictions
    • Tablado
    • Musical creation around Outer Space
    • Campo Abierto
    • Musical creation around Dream Work
    • Biotope
    • EROR
    • IDEA
    • Artistic Research Residency
    • Artistic Residencies: The Blog
    • Rendez Vous 20.21
    • Season 2021.22
    • Seasons from 1996 to present
    • ManiFeste-2022 Website
    • Replay: ManiFeste-2022 Concerts
    • ManiFeste festival from 2012 to 2022
    • L’Étincelle, IRCAM’s journal of creation
  • Transmission

    In parallel to its fundamental missions of research and creation, IRCAM is committed to sharing its knowledge and know-how, its technologies with the general public. Cutting-edge research and diffusion of innovations, an international reference for education and the democratization of artistic practices are the driving forces behind the institute’s educational activities.

    • 2022.23 Training Courses
    • Max, Max for Live
    • OpenMusic
    • Modalys
    • TS2 and Partiels
    • Sound spatialization
    • From PureData to audio plugins
    • Sensors, Interfaces, and Interactive Machine Learning
    • Other training programs
    • Practical Information
    • Advanced Programs
    • Cursus Program on Composition and Computer Music
    • Supersonic Chair
    • Master ATIAM
    • Sound Design Master's Program
    • Music Doctorate
    • AIMove Master
    • School Programs
    • Studios of Creation
    • Mixed-Music
    • Artistic and Cultural Education
    • Career Discovery Visit
    • Images of a Work Collection
    • ManiFeste-2022, the Academy
  • Innovations

    At the center of societal and economic concerns combining culture and information technologies, the current research at IRCAM is seen by the international research community as a reference for interdisciplinary projects on the sciences and technologies for sound and music, constantly exposed to society’s new needs and uses.

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  • Post-doc position for specialist in audio signal processing and machine learning






Post-doc position for specialist in audio signal processing and machine learning

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Short term contract


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Candidacies: until Aug. 26, 2022
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INTRODUCTION TO IRCAM :

IRCAM is a non-profit association, associated with the Centre National d'Art et de Culture Georges Pompidou and located in Paris at 1, place Igor Stravinsky, 75004 PARIS. Its missions include research, creation and pedagogical activities on 20th century music and its relationship with science and technology.

PROJECT DESCRIPTION :

Within the framework of the HAIKUS research project financed by the ANR (French National Research Agency), IRCAM is recruiting a Research and Development Officer on a 12-month fixed-term contract. The objective of the HAIKUS project is the joint exploitation of machine learning (ML) and audio signal processing methods to solve acoustic problems encountered in audio augmented (AA) reality applications. In particular, the AA methods are applied to automatically identify the acoustic channel between one or more sources and the listener. The three main objectives of the project are (a) the blind estimation of the acoustic cues of the room and/or its geometry from the observation of the reverberated audio signals emanating from the sources present in the room, (b) the inference of rules for modifying the spatialization  parameters or interpolating room impulse responses according to the listener's movements, and (c) the blind estimation of the listener's HRTFs from the binaural signals captured in the environment thanks to in-ear microphones. In the framework of this project, IRCAM is more particularly interested in this last objective, but the links with the two previous questions are naturally important.

The project is coordinated by IRCAM and brings together the LORIA in Nancy and the MPIA laboratory of Sorbonne University. These three laboratories share expertise in audio signal processing, machine learning, acoustic imaging and modeling, and binaural technologies.

The project takes place within the Acoustic and Cognitive Spaces team (EAC), integrated into the UMR STMS IRCAM/CNRS/Sorbonne University/Ministry of Culture. The EAC team (Acoustic and Cognitive Spaces) is particularly interested in the analysis/synthesis and perception of immersive sound scenes.

POSITION DESCRIPTION :

  • Automatic selection of HRTFs (Head Related Transfer Functions) among public HRTF databases from binaural recordings in unsupervised conditions (non anechoïc conditions, unknown signals, moving sources, moving listener).
  • Tests and improvement of DNN algorithms developed in the team applied to simple real-world use cases (single source, moderate and diffuse reverberation).
  • Extension of the DNN algorithms for automatic HRTF estimation, i.e. without relying on measured HRTFs databases.
  • Extension of previous methods and algorithms in order to take into account environments with significant first reflections.
  • Contribution to the development/recording of training and test databases.

REQUIRED EXPERIENCES ET SKILLS :

  • The candidate should have a PhD degree with a strong component in machine learning and audio signal processing.
  • Extensive knowledge of deep learning algorithms and experience with their application to the audio domain.
  • Excellent knowledge of Python and Tensorflow.
  • Good knowledge of Linux and Mac OS X.
  • Excellent level of English.
  • Experience in writing peer-reviewed journal/conference papers.

SALARY : According to background and experience.

DEADLINE FOR APPLICATION: August 26, 2022

Please send a cover letter with reference 2022_HAIKUS, a CV detailing the level of experience/expertise in the above-mentioned areas (and any other relevant information) and letters of recommendation to  postdoc_EAC_Haikus_2022@ircam.fr

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