Post-Doc on Deep Learning Perception for Human-Robot Interaction at LIRMM Montpellier, France (24 months + possible extension)
In the context of our new EU project H2020 SOPHIA (2020-2024), we are looking for a highly motivated postdoctoral researcher to conduct studies on vision-based estimation of human posture for Human-Robot Interaction.
The selected candidate will work at LIRMM, a cutting edge laboratory of Robotics located in vibrant and sunny Montpellier.
Provide a vision-based estimator (software library) of the human worker state.
This library should estimate the centre of pressure position, as well as the complete human posture, including limb poses and hand gestures.
The framework must operate at a frame rate that is sufficiently high for robot control.
It should rely on RGB-D sensing as well as (when needed) on other sensing modalities (e.g. force - when interacting with the robot).
- PhD in Computer Science or (alternatively) Robotics or Control Systems (but with strong programming skills)
- strong expertise in deep machine learning (specifically convolutional neural networks and recurrent neural networks)
- excellent programming skills in C++/Linux (if possible for real-time application)
- excellent publication record
- good knowledge of existing deep machine learning architectures
- good knowledge of signal processing: synthesis of observers (Kalman, etc.), noise filtering
- excellent analytical skills & critical thinking
- very good English skills, written and spoken
- above average team & communication skills
Not required but beneficial: hands-on experience with robotic platforms, robotic software frameworks, and sensors
Interested candidates should submit the following by email before the end of February 2020 in a single PDF file to: email@example.com
1. Curriculum vitae with 2 references (recommendation letters are also welcome)
2. One-page summary of research background and interests
3. At least three papers (either published, accepted for publication, or in-preparation) demonstrating expertise in one or more of the areas mentioned above
4. Doctoral dissertation abstract and the expected date of graduation (for those who are currently pursuing a Ph.D)