Two early stage researcher positions (PhD students) in Machine Learning and Biosignal Processing
We are looking for two early stage researchers (fully funded for 4 years) in the area of Machine Learning and Biosignal Processing within the framework of the Collaborative Research Center (CRC) EASE funded by the German Research Foundation (DFG). The candidate will become a member of the graduate program of the CRC at the Universität Bremen (Germany) with the purpose of successfully completing a PhD degree in Computer Science. The CRC "Everyday Activity Science and Engineering" (EASE) is a fundamental research endeavor to investigate the cognitive information processing principles employed by humans to master everyday activities and to transfer the obtained insights to models for autonomous control of autonomous robotic agents. The aim of EASE is to boost the robustness, efficiency, and flexibility of various information processing subtasks necessary to master everyday activities by uncovering and exploiting the structures within these tasks. As one of three major research pillars, research area H “Descriptive models of human everyday activity” aims to understand how people perform vaguely formulated everyday activities.
Based on state-of-the-art machine learning techniques and an existing biosignal processing framework available at Cognitive Systems Lab, the task is to develop and implement unsupervised and semi-supervised learning algorithms that interpret high-volume multimodal biosignal data of humans performing everyday activities. It includes the acquisition of a large-scale data collection on everyday activities consisting of biosignals related to speech, motion, muscles and brain activity. This task will be carried out in collaboration with several Early Stage Researcher fellows.