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Fully funded PhD position in Robot learning

Fully funded PhD position in Robot learning

Position
PhD-student
Department(s)
Mechanical Engineering
FTE
1,0
Date off
14/03/2021
Reference number
V35.4811

Job description

Eindhoven University of Technology is looking for a PhD to strengthen its research on model-driven engineering and machine learning applied to (distributed) robotic and cyber-physical systems.

Perception and cognitive capabilities of robotic systems are ever increasing. Advances in robotic sensing technologies, AI, machine learning, and model-driven engineering create the expectation that such systems will be able to perform in a (semi)autonomous way highly specialized, safety-critical tasks with, at least, similar performance as humans.

In this project we want to develop disruptive approaches to robot learning (e.g., reinforcement learning and learning from demonstration in combination with digital twin technology) for safety-critical robotic systems. With particular emphasis on scalability of the solution. This will allow to develop robotic systems that are safer, are more adaptable to the environment in which they are deployed and can be developed in an easier and faster way by industry. As examples, think about cognitive robots for care (e.g., nursing robots) and cure (e.g., image guided therapy systems) but also for logistic operations where contact with humans is unavoidable (e.g., warehouse logistics and last mile delivery).

You will demonstrate the modelling (digital twin) and learning approaches developed during your project with state-of-the art medical robots. You are also expected to interact and align requirements with architects from leading medical robotics companies.

In addition, you will also be part of the EAISI (Eindhoven Artificial Intelligence Systems Institute) digital twin lab where you can seek application of the methods you develop in other domains such as fleets of mobile robots.

TU/e will offer you plenty of opportunities for development. You can join the DISC (Dutch Institute for Systems and Control) school as well as several programs offered by TU/e for personal development.

We are looking for a very motivated candidate with eagerness to learn and approach problems from a fundamental as well as a practical perspective. When selected you will join the CST group of the Mechanical Engineering Department.

The Control Systems Technology group as part of the department of Mechanical Engineering (ME) has an internationally recognized reputation in mechatronics, precision motion control and robotics. CST targets areas in Precision Machines, Robotics, Biomedical and Automotive engineering by designing performance based controllers, intelligent machine and algorithm designs. CST has a track record of over twenty years in bringing state-of-the-art systems and control theory into new designs and high-tech applications.

The CST group has a track record in European projects. It was coordinator of the
FP7 – ROBOEARTH project, is and has been participating in H2020 projects EUREYECASE, ROPOD, AUTOPILOT and more recently SAFE-UP and many more European and nationally funded projects (INTEREG, OPZUID, FAST).

Since 2005, CST is the main contributor to the TU/e RoboCup team, named Tech United, 
5 times world champion (’12, ’14, ’16, ’18, ‘19) in the Middle Size League and the 2019 world champion in the @Home Domestic Platform League with the TOYOTA Human Support Robot. The model-based, multidisciplinary-oriented approach has proven to be highly valuable in the field of robotics. The CST group is led by Prof. M. Steinbuch and has produced 5 start-ups in the past 10 years (Preceyes, MicroSure, Eindhoven Medical Robotics, Smart Robotics and recently RUVU- behavior for robots).

Job requirements

  • A master’s degree (or an equivalent university degree) in Physics, Computer Science, Electrical Engineering, Mechanical Engineering or a related discipline
  • A research-oriented and proactive attitude.
  • Good programming skills in python and/or Matlab/Simulink
  • Experience in reinforcement learning and ROS is a plus
  • Ability to work in a team and keen on collaborating with industrial partners
  • Excellent written and oral communication skills in English.
  • Proactive and entrepreneurial mind-set, getting things done mentality.
  • Active former membership of student teams participating in RoboCup are considered as a big plus.

Conditions of employment

  • A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
  • A full-time employment for four years, with an intermediate evaluation after one year.
  • To support you during your PhD and to prepare you for the rest of your career, you will have free access to a personal development program for PhD students (e.g., PROOF program).
  • A gross monthly salary and benefits in accordance with the Collective Labor Agreement for Dutch Universities.
  • Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
  • A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
  • Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.

Information and application

More information

Do you recognize yourself in this profile and would you like to know more? Please contact
dr. Elena Torta, e.torta[at]tue.nl

For information about function and terms of employment, click here or contact HR advice ME,
hradviceme[at]tue.nl or HR Services, hrservices.gemini[at]tue.nl.

Please visit www.tue.nl/jobs to find out more about working at TU/e!

Application

We invite you to submit a complete application by using the 'apply now'-button on this page.
The application should include a:

  • Cover letter in which you describe your motivation and qualifications for the position.
  • Curriculum vitae, including a list of your publications and the contact information of three referees.
  • Your MSc thesis.
  • A list of grades for bachelor and master.
  • Optionally letter(s) of recommendation.

Screening of applicants will start as soon as applications are received and will continue until the positions have been filled.

We do not respond to applications that are sent to us in a different way.

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