Job Information
Organisation/Company: Le Mans Université Department: LIUM Research Field: Educational sciences, Neurosciences, Psychological sciences » Psychology, Computer science Researcher Profile: Recognised Researcher (R2) Positions: Postdoc Positions Application Deadline: 1 Nov 2026 - 23:59 (Europe/Paris) Country: France Type of Contract: Temporary Job Status: Full-time Offer Starting Date: 4 Jan 2027 Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job…
related to staff position within a Research Infrastructure? No
Offer Description
Position level : A
Employment establishment : Université du Mans, Avenue Olivier Messiaen, 72085 LE MANS CEDEX 9
Research laboratory : LIUM - Laboratoire d'informatique de l'Université du Mans - EA403
Job : Searcher (The standard job description can be consulted at this link, on pages 1738 et seq., under reference FPRCH007. This document details the main tasks associated with the occupation, as well as the skills, interpersonal abilities and special features that may be required. )
Description of the research subject
This position is part of the ANR project SimFi-Ed, which aims to study the neural correlates of distraction in virtual reality, and more specifically the EEG characterisation of attentional mechanisms related to simulation fidelity and the prediction of distractibility from gaze.
Planning research project
The ANR SimFi-Ed project is scheduled to run from November 2026 to May 2030. The proposed contract is scheduled to run from January 4, 2027, to January 3, 2029.
Phase 1: a) Develop and conduct an experimental protocol for EEG data capture invovling participants viewing scenes with visual defects predicted to affect visual attention (7 months). b) Process the data and analyze it to identify attentional mechanisms linked to visual distraction (6 months).
Phase 2: in collaboration with a PhD student in computer science, a) Develop and conduct a similar second experimental protocol combining, this time, EEG and eye-tracking measurements placing participants in realistic virtual reality environments, still presenting visual defects (3 months). b) Data processing and correlating EEG and gaze data with the aim of identifying ERP/gaze links predictive of visual distractions (4 months). c) Development of a "distractibility index" based on data from the previous step (5 months). d) Write a report presenting the results and findings of phase 1 and 2 (3 months).
Assigned activities and expected results
1. Characterise the neural mechanisms of fidelity-related distraction. Design and run an EEG study in VR (50 participants) in which scenarios systematically vary simulation fidelity, e.g., object-placement incongruities and lighting inconsistencies. Participants perform an anomaly-detection task in a block design presenting isolated objects and objects in scenes in succession. Brain activity is recorded with a mobile EEG system compatible with VR headset.
2. Relate neural activity to gaze and build a distractibility index. Run a second study (40 participants) replicating a scene-exploration protocol with simultaneous recording of mobile EEG and eye tracking in VR, in order to carry out fixation- and saccade-locked ERP analyses.
Analyse the relations between oculomotor features and ERP components, for example, using representational similarity analysis (RSA) in order to identify the components that consistently correspond to gaze patterns and to compare defect types with one another. Contribute, with the PhD student, to building a machine-learning model predicting an ERP-coded signal from gaze data.
3. Disseminate the results. Write journal articles (e.g., Journal of Cognitive Neuroscience, Brain and Cognition, Visual Cognition, Journal of Vision) and conference papers (e.g., Society for Neuroscience, Cognitive Neuroscience Society, ECVP).
To apply for this position, please consult the job description by clicking on this link
The application must include the following documents :
- Detailed curriculum vitae
- Cover letter
- Doctoral degree
- Letters of Recommendation or References
A translation of the application documents must be attached if they are not in French.
The deadline for submitting applications is November 1, 2026. Application files must be sent to Erwan DAVID at the following email address: erwan.david@univ-lemans.fr or by clicking this link.
Where to apply
Requirements
Research Field: Neurosciences — Education Level: PhD or equivalent
Research Field: Educational sciences — Education Level: PhD or equivalent
Research Field: Computer science — Education Level: PhD or equivalent
Research Field: Psychological sciences » Psychology — Education Level: PhD or equivalent
Skills/Qualifications
- hands-on EEG experience: protocol design, acquisition, preprocessing, ERP analysis;
- experience with mobile EEG or EEG in virtual reality is an asset;
- solid skills in statistics and experimental design;
- skills in machine learning applied to neural signals (EEG decoding, RSA) are an asset;
- experience with eye tracking and/or virtual reality (Unity) is an asset;
- fluent English (written and spoken);
- autonomy, rigour, and a taste for interdisciplinary work.
Specific Requirements
Equipment: mobile EEG system dedicated to the project, VR headsets with integrated eye tracking (Varjo; HTC Vive Focus Vision), dedicated computing workstation.
Budget for participant compensation, open-access publication, and attendance at international conferences.
Multidisciplinary team (computer science, learning analytics, vision science, cognitive neuroscience).
Additional Information
Benefits
The contract is for a term of two years. The start date is January 4, 2027. The gross monthly salary ranges from €3,300 to €3,390, depending on experience.
Eligibility criteria
PhD or equivalent
Selection process
- Please submit the required documents at the latest November 1, 2026, to the following email address: erwan.david@univ-lemans.fr or by clicking on this link.
- Pre-selection ;
- Shortlisted candidates will be invited to an interview.
Additional comments
Trips to the University of Munich planned for research and training purposes.
Website for additional job details: https://iut-laval.univ-lemans.fr/fr/recherche-et-innovation/laboratoires/lium.html
Work Location(s)
Number of offers available: 1
Company/Institute: Le Mans University
Country: France
City: Laval
Postal Code: 53000
Street: 52 Rue des Docteurs Calmette et Guérin
Contact
City: LE MANS
Website: http://www.univ-lemans.fr/fr/index.html
Street: Avenue Olivier Messiaen
Postal Code: 72085
E-Mail: drh-post-doc@univ-lemans.fr