[robotics-worldwide] [jobs] Postdoc/RA Positions studying DRL in Logistics at CUHK/HKCLR
The Robotics Learning Group is a new group at the Department of Mechanical and Automation Engineering at the Chinese University of Hong Kong. The group is working under the newly established (Hong Kong) Center for Robotics Logistics (HKCLR), which has as an aim the advancement of robotic technology and its application to real-world logistic scenarios.
HKCLR brings together experts from all areas in robotics, sensors, control, and learning in a deeply collaborative and synergistic manner in the hopes to make significant contributions to the field as well as the transfer of technology to industry.
The Robotics Learning Group is looking for 1 Research Assistant and 1 Post-doctoral fellow to advance state-of-the-art deep reinforcement learning algorithms for more robust and efficient large-scale logistic solutions such as bin picking, conveyor sorting, loading, and unloading in real-world environments.
In particular, we are interested in leveraging invariant and equivariant principles to learn to multiply a robot's experience throughout the state-action space across algorithms and settings. We are also interested in better understanding of causality and invariant factors to lead to better learning algorithms.
We are looking for people with strong backgrounds in programming, machine learning, and deep learning or candidates who have shown very promising potential to join us in advancing the state-of-the-art in DRL.
Candidates must have a (I) Ph.D. degree in C.S., E.E., Mech. E., Robotics, or related field, (ii) a strong publication record, and experience in deploying advanced machine learning or probabilistic robot solutions, (iii) have graduated from a top 100 University, and (iv) a passion for advancing learning.
Research Assistant candidates will be appointed via HKCLR and have an honorary position at CUHK MAE. Ideal candidates will have a demonstrated capacity to realize challenging deep reinforcement learning algorithms and deploy large scale solutions. Worldwide competitive salaries are available and commensurate with experience.
Interesting candidates should send their complete CV, top publications, and project portfolio to Dr. Juan Rojas at juan [dot] rojas [@] cuhk [dot] edu