Dear colleagues, there is a new offer for an interdisciplinary Machine Learning / BCI / Robotics PhD position in Freiburg. Please circulate it in your lab and email lists. Thanks a lot, Michael --- snip --- Doctoral Research Position at the University of Freiburg, Germany The University of Freiburg invites candidates to apply for a fully funded three-year PhD position (TV-L E13). The job offers a novel perspective to relevant problems in robotics in an inter-disciplinary approach involving engineering, artificial intelligence / machine learning, neuroscience and assistive technology. The interaction between a (semi-autonomous) robotic device (e.g., a robotic wheelchair) and a human user is often ruled by a set of strategies executed by the robot. Typical robotic tasks are to accomplish a navigation task, to map the environment or to manipulate objects of the environment. The user may either control the actions of the robot or be an interaction partner for the robot. The level of control the user has over the robot's actions can be placed on the continuum between absolute low-level control (e.g., a joystick), over mid-level control ("turn right on next occasion") up to high-level control ("take me to the kitchen"). While state-of-the-art robotic control already takes the changing environment into account before strategies are selected and executed, the internal state of the user and fluctuations thereof typically are disregarded. Examples of informative mental states of users would be the level of task-induced workload, the sense of control/agency in the current situation or the perceived complexity of the current situation. In the project, relevant internal mental states of the user shall continuously be assessed. Therefore, electrophysiological recordings (e.g., EEG, MEG, GSR, HRV, etc.) will be exploited with methods developed in the field of brain-computer interface (BCI) systems. Upon successful decoding of a mental state of interest, the robotic behavior can be adapted specifically to an individual user and to the perceived situation. Using the resulting co-adaptive strategy between human and robot, we expect an enhancement of usability and user acceptance during various tasks in human-robot interaction. During the project, expected tasks will comprise offline experiments with assessment of electrophysiological signals, simulated robotic control, offline and online data analysis with BCI methods, online experiments with a robotic application and mental state monitoring, evaluation of adaptive strategies of the robot. The candidate is expected to actively participate in the dissemination of research results in publications, on conferences and by teaching. The target group are candidates with a degree at master level in robotics, computer science, artificial intelligence / machine learning, electrical engineering or cognitive science, with a strong relation to science, technology or innovation studies. Candidates are expected to have practical experience in all of the three fields robotics, machine learning/AI, and Brain-Computer Interfaces. We furthermore expect outstanding qualifications, the motivation to obtain a Doctoral degree and the interest to work in an interdisciplinary environment. Finally we require applicants to have excellent communication skills in English. Applications should be send to ais-applications@informatik.uni-freiburg.de. The application documents should consist of a single PDF file and include - Motivation letter (Expose, respectively) - Two letters of recommendation from professors or persons authorized to supervise dissertation projects - Curriculum vitae - Copies of the following documents: a. Higher education entrance qualification (school-leaving certificate) b. University examination certificates (intermediate examinations) c. University diploma d. Any documents providing evidence of academic achievements, relevant practical experience, and qualifications earned at or outside of the university Further information can be obtained from Wolfram Burgard and Michael Tangermann ({burgard|tangerm}@informatik.uni-freiburg.de).