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-UAS technologies o Multi-agent systems and swarm robotics o Autonomous navigation and guidance o Computer vision and perception o Machine learning
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), machine learning algorithms, and perception methods can improve the autonomy, robustness, and precision of robotic manipulation in challenging environments. The project lies at the intersection of control
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operation and maintenance of equipment Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer
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related field. Experience in robotic perception, control, or learning-based methods. Proficiency in Python and C++ for AI and robotics applications. Familiarity with robotic middleware (e.g., ROS, MoveIt
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. Develop AI, machine learning, optimisation, and decision-support algorithms. Build digital twin environments, physics-based modelling, concept evaluation frameworks, and technical risk assessments. Develop
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. Experience with statistical modelling, signal processing, or machine learning. Interest in active perception, surface exploration, and computational neuroscience. Eligibility criteria Applicants must satisfy
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navigation and perception systems. As a key aspect of this role, you will have the unique opportunity to gain hands-on experience in developing and maintaining software solutions for our existing automated
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Understanding of & ability to contribute to broader management/administration processes Experience developing & applying machine learning models to computer vision tasks Practical experience in computing
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, multimodal sensing, LiDAR processing, or infrastructure monitoring is required. Familiarity with machine learning, large language models, agentic AI, AI-based perception, and data integration is important
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robots, robotic manipulators, or locomotion systems. Knowledge of machine learning, reinforcement learning, imitation learning, or computer vision techniques for robotics applications. Strong analytical