Postdoctoral Researcher In Cognitive And/Or Computationnal Neuroscience M/F

Universities and Institutes of France

France

September 28, 2022

Description

  • Organisation/Company: CNRS
  • Research Field: Neurosciences Psychological sciences › Cognitive science Psychological sciences › Psychology
  • Researcher Profile: Recognised Researcher (R2)
  • Application Deadline: 28/09/2022 23:59 - Europe/Brussels
  • Location: France › GRENOBLE
  • Type Of Contract: Temporary
  • Job Status: Full-time
  • Hours Per Week: 35
  • Offer Starting Date: 01/01/2023
  • Main activities: - Theoretical and methodological work on language/memory neurocognition and Deep Learning - Handling of external and internal databases - Work on functional language and memory data to implement the pre-trained model - Testing the model on other data not used for training - Valuation of results (publications, national and international communications)

    Integration of multimodal data, cognitive and inter-cognitive modeling with artificial intelligence approaches Project description and estimated completion date: The integration of multimodal data to elucidate the neural processes and networks underlying cognition and behavior represents a major challenge in cognitive neuroscience. This comes in a current paradigm shift, with recent neurocognitive models considering that human behaviors are best understood if (a) a fusion of data from multiple modalities and (b) consider the complex interactions between cognitive functions. It is therefore fundamental to combine multiple sources of data, both behavioral, cognitive and brain. Their fusion can reflect multiple facets of cognition and the brain, allowing new properties of the system to emerge, intrinsically multimodal. Missions: Objective of the postdoctoral project: (a) Use AI Deep Learning to develop a pre-trained model on large databases (specified data) available in open-source, which can then be applied to local databases, (b)) compare the results with those of other ML-type machine learning methods. Overall, the postdoctoral researcher will carry out theoretical and methodological work focused on Deep Learning in the area of language/memory neurocognition. Objective result(s) setting the end of the agent's mission: (a) implementation of the pre-trained model on the open-source database (January 2023) and application to other databases of the laboratory (June 2023), valorization of results (September 2023).

    -Description of the structure: The Laboratory of Psychology and NeuroCognition, LPNC UMR is a joint research unit (UMR) structured in five thematic research teams (Vision & Emotion, Body & Space, Language, Memory and Development & Learning). Our research activity in Cognitive Sciences is multidisciplinary, thanks to a combined and complementary approach of disciplines belonging to the fields of human and social sciences (such as psychology, linguistics, neuropsychology), engineering sciences applied to cognition (such as mathematics, bio-inspired modeling and signal processing) and life sciences (such as neurosciences, medical sciences or neuroimaging). Our laboratory has more than 120 permanent and non-permanent staff. LPNC website: https: // lpnc.univ-grenoble-alpes.fr/

    Team description: Work in the Language team https: // lpnc.univ-grenoble- alpes.fr/recherche/equipes-recherche/langage. More specifically, in this team and in relation to the theoretical framework proposed in this thesis, Pr. Monica Baciu (https: // lpnc.univ-grenoble-alpes.fr/membre/monica-baciu) has set up a working group including other postdocs, PhD students and engineers. The work proposed in this project, aims to capitalize on the achievements of this group using multi-modality to study neurocognition and more particularly in the continuity of the REORG project, which allowed to propose the L∪M model, to develop a multi-modal pipeline for neuroimaging data analysis, and to gain a proven experience in the field of AI, with robust statistical and mathematical approaches that we have already applied in our previous work (Roger et al., 2019, Roger et al., 2019, Torlay et al., 2017). Other project collaborators: Pr. Martial Mermillod (https: // lpnc.univ-grenoble- alpes.fr/membre/martial-mermillod), Laurent Torlay IE CNRS and Sonja Banjac post-doctoral fellow. Dr. Marine Reyboz (IR CEA) and Dr. Sophie Achard (LJK researcher https:// mistis.inrialpes.fr/people/achard/) will also be involved in this research work.

    Eligibility criteria

    Priority expected skills: Neurocognition theoretical knowledge language and memory; Methodological knowledge in classical statistics and programming; Full mastery of the Python language (PyTorch and/or Tensor Flow) will be absolutely necessary at the time of taking up the position; Deep Learning AI knowledge/experience; English (B2 or C1); Teamwork, interactions with lab members Possible additional skills: Experience with neuroimaging data Previous education, diplomas: PhD degree: cognitive and/or computational neurocience; cognitive sciences Experience with neuroimaging data, with AI Deep learning methods

    Web site for additional job details

    https: // emploi.cnrs.fr/Offres/CDD/UMR5105-GUYOMN0-036/Default.aspx

    Required Research Experiences
  • RESEARCH FIELD
  • Neurosciences

  • YEARS OF RESEARCH EXPERIENCE
  • 1 - 4

  • RESEARCH FIELD
  • Psychological sciences › Cognitive science

  • YEARS OF RESEARCH EXPERIENCE
  • 1 - 4

  • RESEARCH FIELD
  • Psychological sciences › Psychology

  • YEARS OF RESEARCH EXPERIENCE
  • 1 - 4

    Offer Requirements
  • REQUIRED EDUCATION LEVEL
  • Neurosciences: PhD or equivalent

    Psychological sciences: PhD or equivalent

  • REQUIRED LANGUAGES
  • FRENCH: Basic

    Contact Information
  • Organisation/Company: CNRS
  • Department: Laboratoire de psychologie et de neurocognition
  • Organisation Type: Public Research Institution
  • Website: https:// lpnc.univ-grenoble-alpes.fr/
  • Country: France
  • City: GRENOBLE
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