Sort by
Refine Your Search
-
Listed
-
Field
-
-edge machine learning, including Large Language Models (LLMs), to enhance decision-making and planning in robotic systems. Qualifications: Applicants must have a PhD in Robotics, Control Theory
-
to improve the autonomy of Field Robotic systems by fusing control theoretic and machine intelligence approaches. Formal models are directly applied in real experimental facilities. We are seeking a Post
-
trajectories and enhance interaction safety and robustness. Learning for Human-Robot Interaction: Integrate machine learning techniques, such as reinforcement learning and generative models, with control theory
-
-Robot Swarms in Unknown Environments. CAIR invites qualified applicants with a doctorate degree in the areas of electrical, or computer, or mechanical engineering, or related field to apply. A strong
-
power (CSP) systems optimization, computational heat transfer and radiative transport using sophisticated numerical modeling and machine learning approaches for forward and inverse problems in radiation