Phd Position F - M Augmentingworkspace Awareness With Passive Bci From Monitoring To Enhancing Team Coordination H/F INRIA
Talence - 33 CDD- Télétravail partiel
- 36 mois
- Bac +3, Bac +4
- Bac +5
- Service public des collectivités territoriales
Les missions du poste
PhD Position F/M AugmentingWorkspace Awareness with Passive BCI : From Monitoring to Enhancing Team Coordination
Le descriptif de l'offre ci-dessous est en Anglais
Type de contrat : CDD
Niveau de diplôme exigé : Bac +5 ou équivalent
Fonction : Doctorant
Niveau d'expérience souhaité : Jeune diplômé
Contexte et atouts du poste
The PhD will BE supervised by two different research
groups. Firstly, the Potioc project-team, part of the Inria Center at the University of Bordeaux, focuses on the
design, development, and evaluation of novel approaches that leverage multimodal interaction to enhance user
experience. This team has specific expertise in the development of Brain-Computer Interfaces (BCIs) (systems
translating measures of brain activity into commands or messages for interactive applications) across various
contexts and applications, such as post-stroke rehabilitation, assistive technologies or User eXperience (UX)
evaluation. The first two supervisors, Fabien Lotte and Sébastien Rimbert, are members of the Potioc projectteam,
which specializes in Brain-Computer Interfaces (BCIs). Both are recognized experts in the field of EEGbased
interaction and neuroadaptive systems, with complementary expertise in machine learning for BCI (Lotte)
and applied cognitive neuroscience and BCI evaluation in clinical and collaborative contexts (Rimbert). The
third supervisor, Arnaud Prouzeau, is affiliated with the ILDA team at Inria Paris-Saclay, which specializes in
collaborative digital environments and the design and development of visualization tools. He is an expert in collaborative
human-machine interaction, notably in Virtual Reality (VR) environments. A collaboration between
these two teams has already been initiated through a preliminary project, which resulted in a recent joint publication
and poster presentation in an international conference [17]. This PhD project will provide an opportunity
to build on that foundation and further strengthen the collaboration between the two groups. In particular, the
two teams have the ideal and complementary set of skills to study markers of collaboration (the speciality of
ILDA) in brain activity, using BCIs (the speciality of Potioc).
Mission confiée
We hypothesize that specific patterns of EEG-based inter-brain synchrony are predictive of collaborative success
or breakdown, and can BE used to support real-time adaptation of shared workspaces. In other words, we
assume that measurable neural correlates of team alignment-or misalignment-exist, and that they can inform
the design of neuroadaptive systems aimed at enhancing human collaboration.
The thesis will address the following research questions :
RQ1 : What EEG markers of collaboration can BE found depending on the nature of the collaborative context,
such as loose coordination, tight coordination, or mutual misunderstanding?
RQ2 : How robust and stable are these neuromarkers across different tasks and individuals, and to what extent
are they influenced by known sources of variability in the EEG and BCI field?
RQ3 : How can we design neurofeedback based on these markers in order to enhance workspace awareness and
avoid misalignment in collaboration?
The overarching thesis objective is to determine whether EEG-based BCIs can provide actionable insights into
the cognitive states of collaborating individuals, and ultimately support more fluid and effective teamwork.
Principales activités
This project first research question will address whether we can identify neurophysiological markers that are
specific to different types of collaborative coupling. In particular, we aim to identify neurophysiological EEG
markers of collaboration across various situations : in loose collaboration, where collaborators work independently,
in tight collaboration, where they engage in the same task and in situation of mutual misunderstanding,
where there is a breakdown in the collaboration. A second, follow-up, research question will BE : are these neuromarkers of collaboration stable and robust across tasks and context. We will notably study the robustness
and stability of these markers throughout different tasks such as validated-collaboration task performed with
mice and keyboard (e.g., as in Prouzeau et al. [16], from the ILDA team) as well as during collaborative (active)
BCI tasks, where two BCI users collaborate in a computer task fully controled using a BCI - i.e., with EEG only
(e.g., as in Bonnet et al. [3], from the Potioc team). We will also study the robustness of these neurophysiological
markers of collaboration both between-users and within-users subject across time and days, due to the well
known EEG and BCI performance variability [6]. Building on this, a third research question could BE considered : how can we design neurofeedback based on these markers of collaborative coupling, in order to enhance
workspace awareness, reduce misalignment and improve mutual understanding during collaborative tasks? If
successful, this approach could benefit high-stakes collaborative environments where failures in coordination
can have critical consequences. Applications include air traffic control, remote medical procedures, or digital
collaborative educational platforms, where detecting and
Compétences
Methodological contribution : We aim to develop a method to measure workspace awareness and its deeper
cognitive process, e.g., focus alignmenent, engagement level and cognitive balance. This measure could BE useful
for various purposes : to quantify the quality of collaborations more objectively, to provide neurofeedback
on the quality of collaboration and thereby improving workspace awareness or to adapt the interaction and
collaboration tools dynamically according to the collaborative coupling estimated. Detecting misalignment in
collaborative processes will also BE valuable for many potential applications. For example, in aviation, where
misalignment in the collaboration has contributed to accidents such as the crash of Air France Flight 447.
Empirical contribution : We aim to identify neurophysiological markers of collaboration across different types
of collaborative coupling. With the experiment conducted, we will BE able to have more insight on how to detect
these markers and study their variabilities. The neurofeedback designed will also BE evaluated in an experiment.
Such experiment contributions will BE in turn brings new knowledge about collaborative couplin, both inHuman
Computer-Interaction and Neuroscience (given the neural markers).
Technical contribution : The measure of collaboration will BE based on EEG data, processed using signal processing
and machine learning algorithms. Indeed, machine learning tools from the BCI field and from network
neuroscience [7, 10] will BE used to identify which inter-brain EEG synchronisation patterns reflect which collaborative
couplings level, in order to BE able to estimate them in real-time, despite the noise and variability of
EEG signals. Such machine learning pipelines will BE shared open-source, as part of offline EEG signal processing
open-source toolboxes in Python (e.g., MNE Python and PyRiemann) and as part of open-source online BCI
software, notably OpenViBE that is being developped at Inria.
Avantages
- Subsidized meals
- Partial reimbursement of public transport costs
- Possibility of teleworking and flexible organization of working hours
- Professional equipment available (videoconferencing, loan of computer equipment, etc.)
- Social, cultural and sports events and activities
- Access to vocational training
- Social security coverage
Rémunération
2300€ / month before taxs
Bienvenue chez INRIA
A propos d'Inria
Inria est l'institut national de recherche dédié aux sciences et technologies du numérique. Il emploie 2600 personnes. Ses 215 équipes-projets agiles, en général communes avec des partenaires académiques, impliquent plus de 3900 scientifiques pour relever les défis du numérique, souvent à l'interface d'autres disciplines. L'institut fait appel à de nombreux talents dans plus d'une quarantaine de métiers différents. 900 personnels d'appui à la recherche et à l'innovation contribuent à faire émerger et grandir des projets scientifiques ou entrepreneuriaux qui impactent le monde. Inria travaille avec de nombreuses entreprises et a accompagné la création de plus de 200 start-up. L'institut s'eorce ainsi de répondre aux enjeux de la transformation numérique de la science, de la société et de l'économie.
Hellowork a estimé le salaire pour ce métier à Talence
Le recruteur n'a pas communiqué le salaire de cette offre mais Hellowork vous propose une estimation (fourchette variable selon l'expérience).
Estimation basée sur les données INSEE et les offres d’emploi similaires.
Estimation basse
29 600 € / an 2 467 € / mois 16,26 € / heureSalaire brut estimé
34 900 € / an 2 908 € / mois 19,18 € / heureEstimation haute
50 000 € / an 4 167 € / mois 27,47 € / heureCette information vous semble-t-elle utile ?
Merci pour votre retour !
- Talence - 33
- CDD
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