Missions

The postdoctoral researcher will participate in the construction and evaluation of virtual tutors (recommendation systems) by working at the intersection of education sciences, psychology, and data engineering.

Activités

The main tasks of the successful candidate will be:
- Designing and selecting teaching strategies
- Designing and analyzing well-being measures
- Experimental deployment on the LabNBook and UNESS platforms
- Scientific analysis and publications

Compétences

Education
- PhD in education, cognitive psychology, occupational psychology/ergonomics, educational technology, or a related field.
- Dual expertise or interdisciplinary experience is a major asset.

Scientific skills
- In-depth knowledge of teaching strategies, learning models, and educational technology.
- Proficiency in the psychology of well-being, motivation, and subjective measurement (validated questionnaires, experimental protocols).
- Experience conducting studies with human learners or participants.
- Skills in experimental methodology, statistics, quantitative/qualitative analysis.
- Appetite for educational AI, LLMs, or data analysis (advanced skills not required but appreciated).

Cross-functional skills
- Interdisciplinary teamwork.
- Ability to communicate with a diverse audience (computer scientists, engineers, and education researchers).
- Organizational skills, reliability in managing cohorts and sensitive data.
- Excellent scientific writing skills.

Contexte de travail

The work will take place at the Grenoble Computer Science Laboratory (LIG), a laboratory with 450 members comprising professors, permanent researchers, doctoral students, and administrative and technical staff. The LIG's mission is to contribute to the development of fundamental aspects of computer science (models, languages, methodologies, algorithms) and to address conceptual, technological, and societal challenges. The LIG 22 research teams aim to increase the diversity and dynamism of data, services, interaction devices, and use cases in order to influence the evolution of software and systems to guarantee essential properties such as reliability, performance, autonomy, and adaptability. Research at the LIG is organized into five areas: Intelligent systems for connecting data, knowledge, and humans; Software and information systems engineering; Formal methods, models, and languages; Interactive and cognitive systems; Distributed systems, parallel computing, and networks.
The successful candidate will work closely with teams specializing in technological education (I. Girault, C. d'Ham), well-being and affective computing (F. Ringeval), and AI experts in education (N. Ibrahim, S. Amer-Yahia). This person will have privileged access to the LabNBook and UNESS platforms (more than 60,000 cumulative users). Close collaboration with AI engineers, doctoral students, post-docs, and academic partners is planned.

The candidate will work on the FeelGoodAI project. The latter aims to rethink educational recommendation systems by integrating dimensions of well-being, motivation, and pedagogical strategies, using small specialized language models (SLMs). This project is funded by the ANR (AAPG 2025), whose project leader is Sihem AMER YAHIA, DR CNRS at the Grenoble Computer Science Laboratory (LIG).

The position is in a sector covered by the protection of scientific and technical potential (PPST) and therefore, in accordance with regulations, requires your arrival to be authorized by the competent authority of the MESR.

Le poste se situe dans un secteur relevant de la protection du potentiel scientifique et technique (PPST), et nécessite donc, conformément à la réglementation, que votre arrivée soit autorisée par l'autorité compétente du MESR.