Archive for November, 2011


2 open postdoc positions in robot learning by imitation and reinforcement at the Italian Institute of Technology (Outdated)

Wednesday, November 9th, 2011

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.


2 open postdoc positions in Machine Learning for Robot Control of Autonomous Underwater Vehicles (AUV) at the Italian Institute of Technology (Outdated)

Wednesday, November 9th, 2011

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.