Starting Date:November 1st, 2019 – February 1st, 2020.
Funding: The H2020 ICT SPRING Project
Contact Point: Xavier Alameda-Pineda
Duration: 2 years and up to 4 years.
To apply: https://jobs.inria.fr/public/classic/fr/offres/2019-02081
General Context: SPRING – Socially Pertinent Robots in Gerontological Healthcare – is a 4-year R&D project fully funded by the European Comission under the H2020 framework. SPRING aims to develop socially assistive robots with the capacity of performing multi-person interactions and open-domain dialogue. The scientific objective of SPRING is to develop a novel paradigm and novel concept of socially-aware robots, and to conceive innovative methods and algorithms for computer vision, audio processing, sensor-based control, and spoken dialog systems based on modern statistical- and deep-learning to ground the required social robot skills. The technological objective of SPRING is to create and launch a brand new generation of robots that are flexible enough to adapt to the needs of the users, and not the other way around. The experimental objective of SPRING is twofold: to validate the technology based on HRI experiments in a gerontology hospital, and to assess its acceptability by patients and medical staff.
The project gathers academic and industrial partners in Italy (Università degli Study di Trento), Czech Republic (České Vysoké Učenı́ Technické v Praze), UK (Heriot-Watt University), Israel (Bar-Ilan University), Spain (PAL Robotics) and France (ERM Automatismes Industriels, Assistance Public Hôpitaux de Paris, and Inria). Frequent travel to visit partners is required (up to 5 times a year).
Mission: The Perception team offers a development engineer position to work in the field of deep learning for multi-modal human-robot interaction. The recruited engineer will have the following missions: develop advanced deep learning software based on state-of-the-art neural network architectures and cloud computing; assist the team researchers to implement their algorithms using advanced deep learning libraries and software packages; ensure software robustness and re-usability; prepare software for data collection and data annotation; install and maintain deep learning computing resources (software and hardware). The recruited engineer will work in close collaboration with the group members (two senior researchers, 4-5 PhD students and three development engineers) and with the SPRING partners.
- Develop deep learning software that is robust and re-usable.
- Advise the Team’s researchers on implementing their deep and machine learning methods.
- Manage the software/hardware computing resources.
Sought Expertise: The candidates should have strong expertise in deep learning software development (Keras, PyTorch), excellent programming skills in Python, very good expertise in data management, and be fluent in English, both written and spoken. Expertise in other programming environments such as C++, Linux background (command line, shell scripting) and good knowledge of cooperative software development (Git, CI, testing, …) is highly welcome.