Dear colleagues,
We currently have an open PhD position to work on geometric methods for data-efficient robot learning for robotic manipulation.
What is this about?This PhD topic is about
investigating and creating new learning methods built on geometric
approaches (such as those based on Riemannian manifolds theory) for
achieving data-efficient learning and robust adaptation of robot
manipulation skills.
Who are involved?The PhD research will be mainly carried out at the
Bosch center for AI located in Renningen (Germany). You will be co-supervised by
Søren Hauberg (DTU),
Gerhard Neumann (BCAI-KIT) and
myself (BCAI),
and you will have the chance to visit their labs as part of your
studies. Moreover, you will interact with top-notch PhD students and
research scientists in our group working on robot control, task
planning, robot vision, deep learning, among other exciting areas.
Who are we looking for?A super motivated and curious
student who loves math, machine learning and robots! We also value
programming experience on C++, Matlab or Python. An MSc degree on
computer science, robotics, artificial intelligence or applied math is a
good fit.
More info about the PhD position and the application process can be found at
https://jobs.smartrecruiters.com/BoschGroup/743999699722876-phd-geometric-approaches-for-data-efficient-robot-learningFor questions, please contact me.
Leonel Rozo
Research scientist @ BCAI
www.leonelrozo.weebly.com