AI Robotics Researcher Jobs

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Lead the research and development of novel deep learning algorithms for vision-guided robotics to enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control by designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation, going beyond simple grasping to sophisticated handling of diverse items. Collaborate with engineers and researchers to translate concepts into robust, physical hardware-deployable capabilities for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms for precise manipulation of complex or deformable objects. Optimize and deploy research prototypes onto physical robotic hardware with software engineering collaborators. Evaluate model performance in simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art computer vision and robot learning advancements to industrial problems. Mentor junior researchers and contribute to the manipulation research roadmap technical direction.

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As a Senior AI Research Scientist for Vision-guided robotics, responsibilities include leading the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks, exploring the intersection of computer vision and robotic control to design systems for dynamic object perception and interaction, creating models integrating visual data to guide physical manipulation beyond simple grasping, collaborating with multidisciplinary teams to translate research into deployable capabilities on physical hardware, researching and developing architectures for visual perception and sensorimotor control in contact-rich scenarios, designing algorithms for precise manipulation of complex or deformable objects, working with software engineers to optimize and deploy prototypes onto robotic hardware, evaluating model performance in simulation and real-world environments for robustness, identifying opportunities to apply state-of-the-art computer vision and robot learning advancements to industrial problems, mentoring junior researchers, and contributing to the technical direction of manipulation research.

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Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control, designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation, moving beyond simple grasping to sophisticated handling of diverse items. Collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities deployable on physical hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms enabling robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.

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Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control to design systems allowing robots to perceive and interact with objects in dynamic environments. Create models integrating visual data to guide physical manipulation beyond simple grasping to sophisticated handling of diverse items. Collaborate with a multidisciplinary team of engineers and researchers to translate concepts into deployable capabilities on physical robotic hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms for precision manipulation of complex or deformable objects. Collaborate with software engineers to optimize and deploy research prototypes on physical robotic hardware. Evaluate model performance in simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.

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Research and develop novel deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms that enable robots to manipulate complex or deformable objects with high precision. Collaborate with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in both simulation and real-world environments to ensure robustness and reliability. Identify opportunities to apply state-of-the-art advancements in computer vision and robot learning to practical industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.

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Lead research and development of novel deep learning algorithms to enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control to design systems allowing robots to perceive and interact with objects in dynamic environments. Create models integrating visual data to guide physical manipulation, including sophisticated handling of diverse items. Collaborate with multidisciplinary engineers and researchers to translate concepts into capabilities deployable on physical robotic hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms for precise manipulation of complex or deformable objects. Work with software engineers to optimize and deploy prototypes on robotic hardware. Evaluate model performance in simulation and real-world environments to ensure robustness. Identify opportunities to apply state-of-the-art computer vision and robot learning advancements to industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.

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Lead the research and development of novel deep learning algorithms that enable robots to perform complex, contact-rich manipulation tasks. Explore the intersection of computer vision and robotic control by designing systems that allow robots to perceive and interact with objects in dynamic environments. Create models that integrate visual data to guide physical manipulation, enabling sophisticated handling of diverse items beyond simple grasping. Collaborate with a multidisciplinary team of engineers and researchers to translate cutting-edge concepts into robust capabilities deployable on physical hardware for industrial applications. Research and develop deep learning architectures for visual perception and sensorimotor control in contact-rich scenarios. Design algorithms to manipulate complex or deformable objects with high precision. Work with software engineers to optimize and deploy research prototypes onto physical robotic hardware. Evaluate model performance in simulation and real-world environments to ensure robustness and reliability. Identify practical applications of state-of-the-art advancements in computer vision and robot learning for industrial problems. Mentor junior researchers and contribute to the technical direction of the manipulation research roadmap.

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Learn to design, deploy, and operate the backbone of AI infrastructure. Work with GPU clusters, high-speed networking, and large-scale Linux systems. Contribute to the architecture of Australia’s first production-scale AI datacentre systems. Collaborate with AI researchers and engineers to shape the next generation of model training environments. Develop new operational and architectural approaches from first principles.