Post-Doctoral Contract M/F : Explainable Ai, Trusted Ai, Ai For Education

Universities and Institutes of France
December 01, 2022
Offerd Salary:Negotiation
Working address:N/A
Contract Type:Temporary
Working Time:Full time
Working type:N/A
Job Ref.:N/A
  • Organisation/Company: CNRS
  • Research Field: Computer science Mathematics › Algorithms
  • Researcher Profile: Recognised Researcher (R2)
  • Application Deadline: 01/12/2022 23:59 - Europe/Brussels
  • Location: France › VILLEURBANNE
  • Type Of Contract: Temporary
  • Job Status: Full-time
  • Hours Per Week: 35
  • Offer Starting Date: 03/01/2023
  • - understand the personalization process implemented - design and develop an interface for teachers to set up the personalization strategy - design and develop a process for explaining the recommendations provided by the system - participate in the writing of scientific articles and the presentation of research results

    This position is part of the COMPER ANR project, whose objective is to design models and tools to implement a competency-based approach to support personalized learning. Bringing together researchers in computer science, humanities and social sciences and practitioners, this project proposes a model for representing competency frameworks that makes it possible to link the pedagogical activities proposed to learners to their competencies, and to develop a competency profile for each learner. These profiles are used to personalize the activities and learning paths, as well as to help the learner to regulate his or her learning, by including motivational levers. The project is based on experiments at different levels (high school, university, CAP) involving skills of different granularity in different disciplines, in order to assess the generality of the proposed models and tools. The personalization process implemented in the project implements a personalization strategy defined by the project team and based on rules, to provide each learner with learning resources adapted to the competency profile developed from their interactions with the learning environment. The objective of the proposed position is to enable teachers to understand the personalization strategy implemented by the system and to set it up to best suit their needs. The aim is therefore to design a parameterization interface and a process for explaining the system's behavior. These explanations should enable the teacher to understand why a resource is proposed, depending on the learner's mastery of skills and objectives, by exploiting the skills repository.

    Reference : Louis Sablayrolles, Marie Lefevre, Nathalie Guin, Julien Broisin. Design and Evaluation of a Competency-based Recommendation Process. Intelligent Tutoring Systems, Jul 2022, Bucharest, Romania. ⟨hal-03642155⟩

    The person recruited will join the TWEAK team of the LIRIS laboratory, located on the Doua campus in Lyon-Villeurbanne and will work under the direction of Nathalie Guin and Marie Lefevre, in collaboration with Julien Broisin (IRIT).

    Eligibility criteria

    We are looking for a person : - with a PhD in computer science in one of the following fields: AI in Education, Knowledge Engineering, HCI, AI - who is interested in digital technologies for education; - who has - strong web development skills - practical experience in the field of software development - knowledge in the field of AI explainability or user appropriation of digital tools; - who is used to collaborating with other researchers; - who has a good level of English (reading, writing and speaking).

    Web site for additional job details

    https: //

    Required Research Experiences
  • Computer science

  • 1 - 4

  • Mathematics › Algorithms

  • 1 - 4

    Offer Requirements
  • Computer science: PhD or equivalent

    Mathematics: PhD or equivalent

  • FRENCH: Basic

    Contact Information
  • Organisation/Company: CNRS
  • Department: Laboratoire d'informatique en image et systèmes d'information
  • Organisation Type: Public Research Institution
  • Website: https://
  • Country: France
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