Post-Doctoral Research Visit F/M Multisensory workspace capture and inference for XR collaboration

Inria; Rennes; Hybride; EUR 32 000 - 42 000; Plein temps

Avantages offerts par ce poste

Partial transport reimbursement

Teleworking after 6 months

Generous leave (7 weeks + RTT) and 10+

Résumé du poste

Inria's Rennes centre invites applications for a Post-Doctoral Research Visit focusing on multisensory workspace capture and inference for XR collaboration. The role sits in the Seamless team within Centre Inria Rennes/IRISA, prioritizing user-centered XR experiences.

The candidate will explore multimodal reconstruction, tactile rendering, and tools to author multimodal experiences, with opportunities to collaborate across international partners and publish in top venues.

Qualifications

• PhD required or near completion in CS, HCI, or a related field.
• Experience in multimodal sensing, XR, and haptic rendering encouraged.
• Strong publication record and ability to work in a multidisciplinary team.

Responsabilités

• Collaborate on multimodal reconstruction and real-time XR inference.
• Develop haptic rendering interfaces and evaluation protocols.
• Publish results and contribute open-source data/software.

Connaissances

XR research

Multimodal reconstruction

Haptics

Machine learning

Python

C#

Human-computer interaction

Formation

PhD in Computer Science or related field

Outils

PyTorch

Unity

Description du poste

Post-Doctoral Research Visit F/M Multisensory workspace capture and inference for XR collaboration

Fonction : Post-Doctorant

The Inria Centre at Rennes University is one of Inria's eight centres and has more than thirty research teams. The Inria Centre is a major and recognized player in the field of digital sciences. It is at the heart of a rich R&D and innovation ecosystem: highly innovative PMEs, large industrial groups, competitiveness clusters, research and higher education players, laboratories of excellence, technological research institute, etc.

Host institution and research team

The candidate will integrate the Seamless team at the at the Centre Inria at Rennes University/IRISA. The Seamless team adopts a multidisciplinary approach in virtual/augmented reality (XR), human perception, human-computer interaction, and human factors, prioritizing the user at the center of the XR revolution. Their work addresses three key challenges: enabling smooth transitions between realities by bridging gaps in perception and interaction for a continuous experience; fostering equal collaboration across realities, ensuring shared awareness and uniform interaction capabilities regardless of individual differences; and advancing implicit, precise evaluation of user experience.

Context

This PhD is framed within the European Horizon Europe project OmenXR, which aims to develop a real-time, multisensory, and human-centered framework for hybrid collaboration in eXtended Reality (XR). To achieve this, OmenXR will first leverage state-of-the-art image-based rendering techniques to enable on-the-fly photorealistic visual fidelity using consumer-grade Mixed Reality (MR) hardware. Additionally, it will create a multisensory experience that anchors all collaborators in a sensory-coherent environment. Finally, OmenXR will utilize real-time reconstruction and understanding to enable novel forms of hybrid collaboration, integrating remote users, teleoperated robots, and intelligent virtual agents.

The candidate will focus on one to the two following research domains:

Multimodal Reconstruction and Inference: The candidate will conduct research on methods for capturing multimodal information from physical environments in real time. This includes leveraging advanced techniques to infer scene properties such as location, object detection, and tactile characteristics from visual data. The work will explore the integration of foundation models to enhance scene understanding and enrich representations with multimodal information, addressing the balance between realism and plausibility.

Haptic and Tactile Rendering: The candidate will design and evaluate haptic interfaces and algorithms to enable spatialized tactile rendering in extended reality. This could involve the creation of modular, lightweight wearable actuators that combine vibrotactile, force-feedback, and skin-stretch mechanisms. Alternatively, cross-modal rendering techniques will be employed to compensate for hardware limitations, and adaptive encoding schemes will balance sensory fidelity with user cognitive load. Effectiveness will be evaluated through quantitative metrics and qualitative user studies.

Furthermore, the candidate will work on user-driven interactive tools for creating and authoring multimodal experiences. This includes developing tools to assist users during the capture process, providing visual feedback and guidance for efficient reconstruction. Additionally, the candidate will explore methods for users to edit captured information, enabling corrections or adjustments for aesthetic or accessibility purposes.

Additional Duties

Joint PhD Supervision: The postdoc will co-supervise PhD students working on related topics within the project, providing mentorship and technical guidance to ensure alignment with the project’s goals.

Research Management: The candidate could contribute to the project management duties, including progress reporting, milestone tracking, and collaboration with international partners. They will also assist in organizing workshops, meetings, and dissemination activities such as publications and conference presentations.

The candidate is expected to produce high-impact publications in top-tier conferences and journals. They will develop functional prototypes of multimodal reconstruction, rendering, or interaction tools and contribute open-source datasets or software to the research community. Strong interdisciplinary collaboration with project partners will be essential.

The ideal candidate will have a strong background in computer graphics, haptics, extended reality, or human-computer interaction, depending on their selected focus. They should possess experience with machine learning, proficiency in programming languages such as Python or C#, and familiarity with user studies and evaluation methodologies.

Excellent communication skills and the ability to work in a multidisciplinary team are required.

Avantages

• Partial reimbursement of public transport costs
• Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)
• Possibility of teleworking (after 6 months of employment) and flexible organization of working hours
• Professional equipment available (videoconferencing, loan of computer equipment, etc.)
• Social, cultural and sports events and activities