PhD Student Position in Robot Learning and Representation Learning

Research / Academic

We are looking for a motivated Ph.D. candidate to strengthen our teams at the computer science department of the VU Amsterdam in the area of robot learning & representation learning. You will be jointly supervised by the Assistant Professors Kevin Sebastian Luck (Computational Intelligence Group) and Shujian Yu (Quantitative Data Analysis Group).

In your PhD project you will consider the development of new deep learning and robot learning methodologies which can be applied across a variety of robotic platforms. With this you will work at the research frontier by investigating how we can optimize, exploit and generalize across a variety of agent embodiments and create novel reinforcement learning and representation learning approaches. Developing such embodied AI methodologies which do not consider the body of the robot to be static, but changeable and exploitable is a challenging endeavor with impact to both industry & science, and a lot of open and exciting research questions. You can expect to work at the intersection of the following areas: Deep Representation Learning, Reinforcement Learning, Information Theory, Robotics. Furthermore, you will have the possibility to apply your research on real robot platforms in our robotics lab, from standard platforms such as the Franka Enigma robot arm to self-developed modular robots.

As a PhD candidate you will have the opportunity to present your findings at international conferences, collaborate internationally and be an integral and valued part of a new team of researchers in the area of robot learning & deep learning in Amsterdam. As such, we aim to support you to start and build your own scientific career, collect teaching experience in relevant courses, and provide funding for this position for 4 years.


Required qualifications:

  • you have completed or are close to completion (about to submit/defend) of your Master in Computer Science, Electrical Engineering, Statistics, Robotics or a related field
  • strong background in Deep Learning, Reinforcement Learning, and/or Information Theory
  • you possess good skills in Python programming
  • have strong oral and written communication skills in English;

The following desirables are helpful:

  • knowledge in relevant fields such as: Information Theory, (Meta) Reinforcement Learning, Foundation Models, Probability Theory, etc
  • experience with robots or continuous control either in the real world or simulation
  • strong mathematical background (eg courses in Lineare Algebra / Analysis)
  • experience with deep learning frameworks such as PyTorch and Tensorflow
  • experience in writing papers for conferences or a high-quality research thesis in the above mentioned topics
  • relevant technical skills: LaTeX, Linux, Mujoco, PyBullet, ROS

As a university, we strive for equal opportunities for all, recognising that diversity takes many forms. We believe that diversity in all its complexity is invaluable for the quality of our teaching, research and service. We are always looking for talent with diverse backgrounds and experiences. This also means that we are committed to creating an inclusive community so that we can use diversity as an asset.

We realise that each individual brings a unique set of skills, expertise and mindset. Therefore we are happy to invite anyone who recognises themselves in the profile to apply, even if you do not meet all the requirements.

Salary Benefits:

A challenging position in a socially engaged organisation. At VU Amsterdam, you contribute to education, research and service for a better world. And that is valuable. So in return for your efforts, we offer you:

  • a salary of € 2.770,00 and maximum € 3.539,00 gross per month in the fourth year, for a full-time employment
  • an employment contract of initially 18 months. If there is sufficient perspective, this will be extended to a total of 4 years. Your dissertation at the end of the fourth year forms the end of your employment contract.

We also offer you attractive fringe benefits and arrangements. Some examples:

  • A full-time 38-hour working week comes with a holiday leave entitlement of 232 hours per year. If you choose to work 40 hours, you have 96 extra holiday leave hours on an annual basis. For part-timers, this is calculated pro rata.
  • 8% holiday allowance and 8.3% end-of-year bonus
  • solid pension scheme (ABP)
  • contribution to commuting expenses
  • optional model for designing a personalized benefits package

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