PHD Position, Human-Computer Interaction, Supélec - IMS Research Group, France

[TheGeek]

PHD POSITION
Supélec - IMS Research Group
2 rue Edouard Belin, 57070 Metz - FRANCE



Title:
Imitation Learning and Task Transfer for Natural Human-Computer Interaction

Description:
Imitation learning (also referred to as apprenticeship learning or learning from demonstration) is a research field aiming at building machines with the ability of performing tasks after having observed a finite number of demonstrations by an expert. Task transfer is similar to imitation learning although the machine and the expert are not supposed to have the same capabilities. Then, the machine has to catch the goal of the expert so as to reach it using any possible ways. Inverse reinforcement learning (IRL) provides a theoretical solution to both these problems. In the IRL paradigm, the expert is supposed to receive rewards while performing the task. Therefore, it is assumed that the expert acts so as to collect a maximum of rewards. Yet, these rewards are hidden to the machine while observing the expert. Instead of imitating the expert in a supervised manner, IRL proposes to discover the reward function optimized by the expert from demonstrations so as to learn in turn a behavior that maximizes the collected rewards. The learnt reward function is a compact representation of the task. Apprenticeship learning via inverse reinforcement learning is a promising research domain in the field of robotics but has not been investigated in the domain of human-machine interaction. Yet, this is an obvious application since to reach naturalness, a human-computer interface (HCI), and especially a multimodal interface, should exhibit a behavior that is close to the one of a human.
The selected candidate will investigate the theoretical foundations of IRL so as to develop efficient algorithms able to learn from a limited number of demonstrations. Then, these algorithms will be applied to build natural human-computer interfaces exhibiting an adaptive and social behavior.

Context:
This research is part of a starting project funded by the European Commission under the FET OPEN program. The ILHAIRE project (Incorporating Laughter into Human-Avatar Interactions: Research and Evaluation) is a 3-year project aiming at studying the role of laughter in human-human and human- machine interactions. The candidate will thus evolve in an international consortium regrouping partners from France, Belgium, Italy, Switzerland, United Kingdom and Germany.

The selected candidate will be hosted within the « Information, Multimodality & Signal » research group on the Metz campus of Supélec. The group is composed of approximately 30 persons involved in machine learning, signal processing and high-performance computing. During the ILHAIRE project, the IMS group is in charge of developing an interaction management system incorporating laughter. The IMS group also conducts researches in the domains of smart environments and robotics and the candidate will benefit from new facilities recently acquired by the campus for developing this research.

Profile
The candidate should hold a Master or engineering degree in electrical engineering, mathematics or computer science; have a good knowledge of machine learning and statistics as well as in C++ programming. Working knowledge of English is mandatory.

Contacts:
Olivier Pietquin olivier.pietquin@supelec.fr
Matthieu Geist matthieu.geist@supelec.fr
IMS homepage: ims.metz.supelec.fr
PhD Position [3y; MSc or engineering degree in electrical engineering, mathematics or computer science; knowledge of machine learning & statistics; C++; English; Imitation Learning and Task Transfer for Natural Human-Computer Interaction] / Supélec - IMS Research Group; Metz

[narges84]

Research fellow (PhD Candidate) in informatics – 2 positions


At the Department of Informatics (http://www.uib.no/ii/en) two 4-year positions as research fellow are available within the field of informatics.

For further information about the position please contact Petter.Bjorstad@ii.uib.no

Applicants must have achieved a master’s degree or equivalent in informatics, or have submitted their master thesis for assessment by the application deadline. It is a prerequisite, however, that the formal admission requirements for the PhD programme are met before appointment can be made.

The research fellow must take part in the University's approved PhD programme leading to the degree within a time limit of 3 years. Application for admission to the PhD programme, including a project plan outline for the training module, will be worked out in collaboration with the research group in question.

In total, the fellowship period is 4 years. For positions with a 4-year duration 25 pct of the period will be designated to teaching and/or administrative duties. The fellowship period may be reduced if the successful applicant has held previous employment as research fellow.

The teaching language will normally be Norwegian. However, applicants with documented excellent knowledge of English are also eligible, regardless of knowledge of Norwegian.

Initial salaries at grade 48 (code 1017/pay framework 20.8) in the Civil Service pay grade table; currently NOK 383,900 gross p.a.; following ordinary meriting regulations.

Women in particular are invited to apply. If, in the opinion of the evaluation committee, several applicants have approximately equivalent qualifications, the rules on equal opportunities laid down in the Personnel Regulations for Academic Positions will be applied.

State employment shall reflect the multiplicity of the population at large to the highest possible degree. The University of Bergen has therefore adopted a personnel policy to ensure that we achieve a balanced age and gender composition and the recruitment of persons of various ethnic backgrounds. Persons of different ethnic backgrounds are therefore encouraged to apply for the position.

The University of Bergen applies the principles of public openness when recruiting staff to scientific positions. Hence, the evaluation committee’s report will be disclosed (in full detail, and not anonymised) to all of the applicants.

Information about the applicant may be made public even though the applicant has requested not to be named in the list of applicants. The applicant will be notified if his/her request is not accepted.

The successful applicant must comply with the guidelines that apply to the position at any time.

Send electronic application by clicking on the button marked "APPLY FOR THIS JOB" on this page.

The application should include a brief statement of research interests and motivation, CV, copies of certificates and diplomas, a list of publications and the names and contact details of at least two referees.

Incomplete applications and applications sent by e-mail will not be considered.

Closing date for applications: 24 June 2011

Quote reference number: 2011/6638