PhD student positions in Robotics @ Computer Science
A more detailed description is currently being formulated. The general areas for the two robotics projects are machine learning for robotic applications, task and work environment representation, skill based robot programming and mobile manipulation. If you have questions, please contact Elin A. Topp, Jacek Malec, or Volker Krüger.
Apart from the formal requirements specified in the official call, the applicant should match the following criteria. The ideal candidate has a solid background in computer science or a related field with very good mathematical and programming skills. Experience in at least one of the following areas is beneficial: Machine Learning, AI Reasoning, Robotics, Human-Robot Interaction, and Programming Languages suitable for Robotics Research and ROS. Besides technical and mathematical skills, the candidate is expected to be curious and ambitious, with strong motivation to conduct research, but also willing to implement for and experiment with actual robotic systems. The applicant should be used to a well-structured work style, and have the ability to work both individually and in teams. Very good communication skills in both oral and written English are required. A short research proposal showing the applicant's interests in relation to the project area should be included in the application material.
In addition to a strong but young interest in mixed-initiative interaction with both mobile (service) and industrial robot systems and the underlying approaches for situation understanding, intention recognition and general interaction monitoring so far represented by Elin A. Topp, the research group for Robotics and Semantic Systems has a well established track record in knowledge representation and management (represented mainly by Jacek Malec) as well as integrated end-to-end software systems for (mainly, but not exclusively) industrial robotic applications (Klas Nilsson and Mathias Haage), and is or has been involved in a series of respective EU-funded projects (SIARAS, ROSETTA, PRACE, SMErobotics, SARAFun). These efforts will now be strengthened further through the upcoming extension of the group.
A second, very strong and well established line of research is pursued by Pierre Nugues in the area of natural language processing (NLP), specifically semantic parsing, role labelling, and entity recognition. Some rather recent efforts of integrating NLP into work on intuitive programming of industrial robots have led to the establishment of an end-to-end support chain from high-level (spoken) commands formulated in natural language through levels of task and skill representation and abstraction down to executable robot code for industrial, both native and external, robot controllers (see Maj Stenmark’s respective publications).
The group is collaborating closely with the robotics researchers within the Dept of Automatic Control, enabling this type of research on all system levels, from investigations of high-level programming tools to sensor-based force-controlled manipulation approaches.
In addition to the opportunities for collaboration through the WASP Graduate School and WASP research topics, the prospective candidate has the opportunity to benefit from the different topics, perspectives, and core competencies offered within RSS and the RobotLab.
Currently, the group is involved in the Wallenberg Autonomous Systems and Software Program by hosting one industrial PhD project (Mårten Lager, "Digital Cognitive Companion for Marine Vessels" within the WASP project "Interaction and Collaboration with Sensor Rich Agents"), supervised by Jacek Malec and Elin A. Topp. Both Jacek and Elin have also been involved as content developers and lecturers in the first edition of the WASP core course "Autonomous Systems". In addition to that, there are currently four other WASP PhD projects hosted at the Department of Computer Science, one of them being another industrial project in collaboration with ARM. Collaboration across the respective research topics would be encouraged.