Application deadline: December 4, 2011.

The Department of Advanced Robotics at the Italian Institute of Technology, an English-language research institute, has 2 postdoc openings in the area of machine learning applied to compliant robot control.

The successful candidates will participate in a new European research project called STIFF-FLOP (STIFFness controllable Flexible and Learn-able Manipulator for surgical OPerations) starting early 2012. The project is a collaboration of 11 universities, research institutes and companies in Europe: KCL (UK), SSSA (Italy), TRI (Spain), PIAP (Poland), HUJI (Israel), UoS (UK), USiegen (Germany), Shadow (UK), FRK (Poland) and EAES (Netherlands).

We are seeking highly motivated and talented candidates who wish to contribute to the development and experimental validation of novel imitation learning and reinforcement learning algorithms applied to a variety of compliant robots available in the Department of Advanced Robotics. These platforms include: a bimanual upper-torso composed of two Barrett WAM manipulators, a KUKA LightWeight Arm and the compliant humanoid robot COMAN.

The developed algorithms will be extended to the challenge of minimally invasive surgery, in which robotic tools must enter through narrow openings and manipulate soft organs that can move, deform, or change stiffness. The successful candidates will concentrate on the learning, collaborative human-robot interaction and/or variable compliance manipulation aspects of this project.

The research will be conducted within the Learning and Interaction Group. Contracts are up to 4 years with respect to the duration of the project. Salaries will depend on experience, with policies providing additional pension and health benefits. Applicants may also qualify for reduced tax benefits. Expected starting date is February 2012.

For further information please contact: Dr Sylvain Calinon (sylvain.calinoniit.it).

IIT is located in Genova, Italy, a seaside Mediterranean city set on the beautiful Italian Riviera, where the cost of living is much more affordable than many other European cities. International applications are encouraged and will receive logistic support with visa issues.

Application Requirements:

• PhD degree in Computer Science, Mathematics or Engineering
• High-quality publications record
• Strong interest in machine learning
• A high level of competence in one or more of the following areas: imitation learning, reinforcement learning, probabilistic models, MATLAB and C/C++ programming
• Experience in robot control is a plus
• Fluency in written and spoken English (IIT is an English language research institute)

 
Application Procedure:

To apply, please send a detailed CV, a statement of motivation, copies of degree certificates, grade transcripts, contact information of at least two references, and other support materials such as reference letters to Dr Sylvain Calinon (sylvain.calinoniit.it) and Dr Petar Kormushev (petar.kormusheviit.it), by quoting STIFF-FLOP in the email.

Deadline of application: December 4, 2011.

The Department of Advanced Robotics has 2 Post Doc openings in the research areas of Reinforcement learning and Imitation learning applied to robot control of Autonomous Underwater Vehicles (AUV).

The successful candidates will participate in a 3-year research project funded by the European Commission under the Seventh Framework Programme (FP7-ICT, STREP, Cognitive Systems and Robotics) called “PANDORA” (Persistent Autonomy through learNing, aDaptation, Observation and ReplAnning) which will start in January 2012.

The project is a collaboration of five universities and institutes in Europe: Heriot Watt University (UK), Italian Institute of Technology (Italy), University of Girona (Spain), King’s College London (UK), and National Technical University of Athens (Greece).

The accepted candidates will contribute to the development and experimental validation of novel reinforcement learning and imitation learning algorithms for specific application to robot control of autonomous underwater vehicles.

The research work includes conducting experiment with AUVs in water tanks in collaboration with the other project partners. The developed machine learning algorithms will also be applied for other robots available at IIT, such as the compliant humanoid robot COMAN, the humanoid robot iCub, Barrett WAM manipulator arm, and KUKA LWR arm robot.

The research will be conducted within the Learning and Interaction Group. The salary will depend on the candidate’s experience. The current range is from 30,000-40,000 Euros per year excluding additional pension and health benefits. Applicants may also qualify for reduced taxes benefits. Contracts are for up to 3 years. Expected starting date is February 2012.

International applications are encouraged and will receive logistic support with visa issues. For further information please contact: Dr Petar Kormushev (petar.kormusheviit.it).

Application Requirements:

• PhD degree in Computer Science, Mathematics or Engineering
• High-quality publication record
• Strong interest in machine learning algorithms
• Strong competencies in some of these areas: machine learning, reinforcement learning, imitation learning, MATLAB and C/C++ programming
• Experience in robot control is a plus
• Fluency in both spoken and written English

 
Application Procedure:

To apply please send a detailed CV, a statement of motivation, degree certificates, grade of transcripts, contact information of at least two references, and other support materials such as reference letters to: Dr Petar Kormushev (petar.kormusheviit.it) and Dr Sylvain Calinon (sylvain.calinoniit.it), quoting PANDORA in the email subject.

There are several open PhD positions at ADVR-IIT for 2012 (deadline for application September 23, 2011).

http://www.iit.it/en/resources/calls/unige/xxvii-cycle-doctoral-school-on-life-and-humanoid-technologies.html

For “Machine Learning, Robot Control and Human-Robot Interaction”, see Stream 3, Themes 2.7 and 2.8, p.22 on the program for Doctoral Course on Robotics, Cognition and Interaction Technologies in this PDF document.

Additionally, a PhD position opening in learning by imitation is advertised below (same instruction as above):

Theme 2.8b: Learning from demonstrations in a soft robotic arm for assistance in minimally invasive surgery

This PhD position will take place within a new European Project starting in 2012, in which the PhD candidate will collaborate with several universities and institutes in Europe. In minimally invasive surgery, tools go through narrow openings and manipulate soft organs that can move, deform, or change stiffness. There are limitations in current robot-assisted surgical systems due to the rigidity of robot tools. A soft robotic arm will be available within the project to manipulate objects while controlling the stiffness of selected body parts. This PhD proposal will focus on the learning, human-robot interaction and variable compliance manipulation aspects.

The objective is to use multiple demonstrations from the teleoperator to learn force/position control manoeuvres so that the teleoperator could, over time, concentrate on high level decisions while the robot takes care of low level reactive control manoeuvres in a semi-autonomous fashion. The PhD candidate will conduct robotic experiments to answer a number of questions in the areas of learning to control the stiffness of selected parts of the body, moving in a constrained space, and to exert desired forces on soft objects with uncertain impedance parameters.

Probabilistic encoding schemes based on Hidden Markov Models will be used to learn a policy that takes into account variability and correlation information collected during consecutive trials. The aim is to estimate an adequate level of compliance depending on the task requirements to leverage the operator with operations that are not directly relevant for the task. The use of novel control algorithms will be explored to arbitrate the degree of coupling of the flexible arm to best suit the statistics of the task (e.g., by stiffening the arm in task relevant dimensions).

Everyone can post articles and comments on this blog by creating an account here.

If you do not receive the confirmation message by email a few minutes later, verify that it has not been redirected as spam.