Post Doc position on Machine Learning for Human-Robot Interaction at University Claude Bernard-Lyon 2022
| PepperMint 22 | |
|---|---|
| Type | Job |
| Categories (tags) | CA, AI, Social Robotics, LIRIS, Machine Learning, Post-doc |
| Dates | - 2022/10/20 |
| Link | https://bit.ly/3FOWGmS |
| Address | University Claude Bernard-Lyon 1 |
| Geolocation | 45° 46' 47", 4° 51' 56" |
| Abstract due | |
| Submission deadline | |
| Final version due | |
| Notification date | |
| Tweet | The PepperMint Project at the University Claude Bernard-Lyon are looking for a Post Doc to join their project team composed of researchers, engineers and practitioners in the field of AI / Social Robotics and CA. Deadline for application: October 20th, 2022 |
| Export for iCalendar | |
Post Doc position on Machine Learning for Human-Robot Interaction at University Claude Bernard-Lyon 2022:
Details:
Opening of Post Doc position on Machine Learning for Human-Robot Interaction @LIRIS-CNRS UMR5205, University Claude Bernard-Lyon1
Duration : 15 months (potentially extensible to 18 months) - Expected starting date January 2023
Team : SyCoSMA at LIRIS-CNRS (UMR 5205), University Claude Bernard-Lyon 1
Project : PepperMint funded by ASLAN Labex
Partners: LIRIS (SyCoSMA, SAARA Teams), ICAR (InSitu Team), University of Oulu-Finland (GenZ),
Supervision: Pr. Salima Hassas , Dr. Mathieu Lefort
Context
PepperMint (Interacting with Pepper: mutual learning of turn-taking practices in HRI) is funded by the ASLAN Labex. It proposes an exploratory study of embodied turn-taking practices in task-related Human-Robot Interaction (HRI) to improve the social abilities of robots and make HRI more natural to humans. The project initiates a cooperation between researchers in AI (Artificial Intelligence) (LIRIS) and CA (Conversation Analysis) (ICAR and GenZ Oulu - Finland).
It investigates if and how CA findings on natural occurring interaction can be used to develop innovative and effective AI models for HRI. The project is grounded in a detailed multimodal analysis of turn-taking in naturally occurring HRI, putting forward the emergence of turn allocation as complex sequential and multimodal practices.
The project is built upon existing works on AI/ML (Machine Learning) algorithms of the state of the art to program an application for reception and orientation of people in a university library. Previously, we recorded human-robot interactions based on a first ad-hoc version of the robot with state of the art algorithms and ad-hoc turn-taking practices. These data are used in CA studies to identify successful interactions. The goal of this post doc is to use this annotated dataset for machine learning methods to propose a new AI model for HRI, coupling developmental learning and CA findings.
The detailed missions of the Post Doc will be: – To review the state of the art algorithms for Turn-Taking. – To collaborate with another Post-Doc in the field of Conversation Analysis, to clean and prepare the annotated data that will be produced by the CA researchers, and create new algorithms for ML according to CA findings. – To develop a new version of the HRI application with new ML (oriented towards Developmental Learning) algorithms to improve turn-taking practices in HRI. – To contribute to the (scientific) communication activities of the PepperMint Project.
Required Skills:
We are looking for a Post Doc to join our project team composed of researchers, engineers and practitioners in the field of AI / Social Robotics and CA.
The ideal candidate will have the following skills and background: – Strong Expertise/Experience/Background in AI and Machine Learning – Good development/programming skills in Object Oriented Programming (e.g. Java, C++, Python) – Fluent or good level in written English� – Open mindness, teamwork, autonomy and capacity to interact with other disciplines like social sciences. – Interest in interdisciplinary research – Knowledge in Social Robotics (Human Robot Interaction) would be a plus
Application
Applications should include a detailed curriculum vitae, a statement of interests and two reference contacts.
Applications and letters should be sent via electronic mail to: Salima.Hassas@liris.cnrs.fr; Mathieu.Lefort@liris.cnrs.fr and heike.baldaufquilliatre@ens-lyon.fr
Deadline for application: October 20th, 2022
(Please note that 2 to 3 months will be taken by the administration for the hiring procedure)
Working environment: The recruited candidate will be employed by: CNRS, Université Claude Bernard-Lyon 1, at LIRIS-CNRS Laboratory, located at Nautibus building, Lyon.
