PhD student position at Umeå University within the NEST project “Intelligent Cloud Robotics for Real-Time Manipulation at Scale”
This project investigates and develops federated contrastive, transformer, and deep learning methods for learning suitable representation and task-based robot manipulation policies at scale. Each robotic node will train on varied representations to perform multiple downstream tasks, e.g., faster model and unseen environment adaption. These uniform representations motivate to develop continual, peer-assisted, deep, and imitation federated learning methods for fusing knowledge from the cloud to edge nodes to achieve high precision performance and low-cost policy training.
The position is aimed for doctoral studies in Computing Science within the autonomous distributed systems lab, but collaboration with researchers in, e.g., machine learning, mathematical statistics, optimization, cloud robotics, deep learning or artificial intelligence is expected.
The position is funded by The Knut and Alice Wallenberg Foundation through The Wallenberg AI, Autonomous Systems and Software Program (WASP) within a new ambitious NEST project “Intelligent Cloud Robotics for Real-Time Manipulation at Scale” in collaboration with KTH, Stockholm and Lund University, Lund.