Unlocking the Secrets of Cognitive Machines
Cognitive robotics and neuro-AI are rapidly evolving fields that hold great promise for advancing human capabilities. As a researcher in this area, you will have the opportunity to explore the intersection of neuroscience, artificial intelligence, and robotics. Your work will focus on developing intelligent systems inspired by cognitive and neural mechanisms, with a particular emphasis on integrating insights from neuroscience into robotic architectures.
The role involves guiding the development of neuro-inspired architectures for adaptive robotic systems, designing learning-enabled control and perception pipelines for complex environments, and applying neuroscience to develop intelligent, embodied systems that exhibit robust adaptation. Additionally, you will integrate multimodal data, such as EEG, MEG, fNIRS, SEEG, and MRI, into cognitive control loops, produce noteworthy publications, patents, and demonstrators, and collaborate with teams in medical robotics, AI, and neurotechnology.
The ideal candidate will have a PhD in Cognitive Robotics, Computational Neuroscience, AI, or related field, with strong publication records in peer-reviewed international journals/conferences. They should possess deep knowledge in at least one of the following areas: Neuro-inspired AI and learning systems, Cognitive architectures and adaptive robotics, or Multimodal signal processing and neurodecoding. Experience with programming languages such as Python and C++, ROS, and robotic platforms or intelligent systems in real-world contexts is also essential.
This position requires a self-driven, pragmatic, and solution-oriented mindset, solid analytical and organizational competencies, commitment to pushing limits and establishing a lasting legacy in neuro-AI and robotics, highly effective English communication skills, and a collaborative spirit and passion for interdisciplinary innovation.