PhD position in perception for robotics and gesture learning
Country/Region : Switzerland
Website : https://www.idiap.ch
Description
The Perception and Activity Understanding group (Jean-Marc Odobez, http://www.idiap.ch/~odobez/) seeks one PhD candidate for a Swiss NSF funded project aiming to study robot skills acquisition through active learning and social interaction strategies (ROSALIS, see below). In the project, the PhD candidate will work on the multimodal perception of persons and objects, and collaborate with two other PhD students working on skill learning and interaction modeling.
The project will start in april 2018, but the position can start earlier. The ideal PhD candidate should hold a MS degree in computer science, engineering, physics or applied mathematics. S/he should have a good background in statistics, linear algebra, signal processing and programming, machine learning. The successful applicant will have good analytical skills, written and oral communication skills, and the ability to work in a multidisciplinary team.
The position is for 4 years, provided successful progress, and should lead to a dissertation. The selected candidates will become doctoral students at EPFL provided acceptance by the Doctoral School at EPFL (http://phd.epfl.ch/applicants). Annual gross salary ranges from 47,000 CHF (first year) to 50,000 CHF (last year).
Interested candidates should submit a cover letter, a detailed CV, and the names of three references (or recommendation letters) through the Idiap online recruitment system: http://www.idiap.ch/education-and-jobs/job-10234.
Interviews will start upon reception of applications until the position is filled.
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About ROSALIS and the PhD position.
Most efforts in robot learning from demonstration are turned toward developing algorithms for the acquisition of specific skills from training data. While such developments are important, they often do not take into account the social structure of the process, in particular, that the interaction with the user and the selection of the different interaction steps can directly influence the quality of the collected data. In ROSALIS, we propose to rely on natural interactions for skill learning, involving queries about the skills, and demonstrations made by both the human and the robot to show what it has learned.
PhD position: Besides research on skills representation and active learning methodologies relying on heterogeneous sources of information (demonstrations, feedback labels, properties), the project will investigate novel perception algorithms to allow natural interactions between the robot and the teacher. The aim is to provide a higher level understanding of the teacher behaviors and intentions through audio, speech, gaze, and gesture (arm, body, head) analysis, in relation with the (unknown) skill she is teaching to the robot. This implies understanding (and distinguishing) her communication signals (yes, no, explanation) including the feedback about and during demonstrations made by the robot, and the multimodal demonstrations (partial or global) she is making of the skill to be learned.
The different mechanisms (skill learning, active learning, perception) will be integrated in a global model of interaction, implying the coordination (selection, timing) of different smaller interaction units. We target applications of robots in both manufacturing (with Baxter and Franka robots) and home/office environments (with the Pepper robot), both requiring re-programming in an efficient and personalized manner.
ROSALIS is a SNSF funded project involving both the Perception and Activity Understanding group (Jean-Marc Odobez, http://www.idiap.ch/~odobez/) and the Robot Learning and Interaction group (Sylvain Calinon, http://calinon.ch) at the Idiap Research Institute (http://www.idiap.ch).
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About Idiap:
Idiap is an independent, not-for-profit, research institute recognized and funded by the Swiss Federal Government, the State of Valais, and the City of Martigny. Idiap offers competitive salaries and conditions at all levels in a young, high-quality, dynamic, and multicultural environment. Idiap is an equal opportunity employer and is actively involved in the "Advancement of Women in Science" European initiative. The Institute seeks to maintain a principle of open competition (on the basis of merit) to appoint the best candidate, provides equal opportunity for all candidates, and equally encourage both genders to apply.
Idiap is located in the town of Martigny in Valais, a scenic region in the south of Switzerland, surrounded by the highest mountains of Europe, and offering exceptional quality of life, exciting recreational activities, including hiking, climbing and skiing, as well as varied cultural activities. It is within close proximity to Lausanne and Geneva. Although Idiap is located in the French part of Switzerland, English is the official working language. Free French lessons are also provided on a complimentary basis.
For frequently asked questions (FAQs) about living in Switzerland, please go to http://www.idiap.ch/en/faq
The project will start in april 2018, but the position can start earlier. The ideal PhD candidate should hold a MS degree in computer science, engineering, physics or applied mathematics. S/he should have a good background in statistics, linear algebra, signal processing and programming, machine learning. The successful applicant will have good analytical skills, written and oral communication skills, and the ability to work in a multidisciplinary team.
The position is for 4 years, provided successful progress, and should lead to a dissertation. The selected candidates will become doctoral students at EPFL provided acceptance by the Doctoral School at EPFL (http://phd.epfl.ch/applicants). Annual gross salary ranges from 47,000 CHF (first year) to 50,000 CHF (last year).
Interested candidates should submit a cover letter, a detailed CV, and the names of three references (or recommendation letters) through the Idiap online recruitment system: http://www.idiap.ch/education-and-jobs/job-10234.
Interviews will start upon reception of applications until the position is filled.
---
About ROSALIS and the PhD position.
Most efforts in robot learning from demonstration are turned toward developing algorithms for the acquisition of specific skills from training data. While such developments are important, they often do not take into account the social structure of the process, in particular, that the interaction with the user and the selection of the different interaction steps can directly influence the quality of the collected data. In ROSALIS, we propose to rely on natural interactions for skill learning, involving queries about the skills, and demonstrations made by both the human and the robot to show what it has learned.
PhD position: Besides research on skills representation and active learning methodologies relying on heterogeneous sources of information (demonstrations, feedback labels, properties), the project will investigate novel perception algorithms to allow natural interactions between the robot and the teacher. The aim is to provide a higher level understanding of the teacher behaviors and intentions through audio, speech, gaze, and gesture (arm, body, head) analysis, in relation with the (unknown) skill she is teaching to the robot. This implies understanding (and distinguishing) her communication signals (yes, no, explanation) including the feedback about and during demonstrations made by the robot, and the multimodal demonstrations (partial or global) she is making of the skill to be learned.
The different mechanisms (skill learning, active learning, perception) will be integrated in a global model of interaction, implying the coordination (selection, timing) of different smaller interaction units. We target applications of robots in both manufacturing (with Baxter and Franka robots) and home/office environments (with the Pepper robot), both requiring re-programming in an efficient and personalized manner.
ROSALIS is a SNSF funded project involving both the Perception and Activity Understanding group (Jean-Marc Odobez, http://www.idiap.ch/~odobez/) and the Robot Learning and Interaction group (Sylvain Calinon, http://calinon.ch) at the Idiap Research Institute (http://www.idiap.ch).
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About Idiap:
Idiap is an independent, not-for-profit, research institute recognized and funded by the Swiss Federal Government, the State of Valais, and the City of Martigny. Idiap offers competitive salaries and conditions at all levels in a young, high-quality, dynamic, and multicultural environment. Idiap is an equal opportunity employer and is actively involved in the "Advancement of Women in Science" European initiative. The Institute seeks to maintain a principle of open competition (on the basis of merit) to appoint the best candidate, provides equal opportunity for all candidates, and equally encourage both genders to apply.
Idiap is located in the town of Martigny in Valais, a scenic region in the south of Switzerland, surrounded by the highest mountains of Europe, and offering exceptional quality of life, exciting recreational activities, including hiking, climbing and skiing, as well as varied cultural activities. It is within close proximity to Lausanne and Geneva. Although Idiap is located in the French part of Switzerland, English is the official working language. Free French lessons are also provided on a complimentary basis.
For frequently asked questions (FAQs) about living in Switzerland, please go to http://www.idiap.ch/en/faq
Last modified: 2017-12-16 22:31:44