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of autonomous mobile machines integrating perception, reasoning, learning, action and reaction capabilities. The team's main research areas are: architectures for autonomous robots, human-robot interaction
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and AI to efficiently design safe systems. This is a postdoctoral position in the fields of AI planning, reinforcement learning (RL), and formal methods. The position is initially funded for 12 months
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perception for robotics; machine learning. o An interest for approaches based on foundation models. o Proficiency in open-source libraries: Pytorch or equivalent, OpenCV, Open3D, PCL, etc. o Programming
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in the Earth's outer core, with implications for deep Earth processes [1]. A variety of inverse methods (data assimilation, machine learning, etc.) has been employed to recover the fluid motions in
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Machine/Deep learning and classification Knowledge of the Linux operating system for using a computing cluster Interest in transdisciplinarity and teamwork Autonomy and scientific rigor Website
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to hydrido-closo-borates,5 from sodium borohydride. Due to unexplained selectivity in boron cluster formation, a detailed mechanistic understanding is necessary. This postdoctoral project aims to explore