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manipulation tasks. We are seeking candidates with a strong background in robotics and machine learning, and demonstrated experience in two or more of the following areas: deep learning, reinforcement learning
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considered for Research Assistant. Strong programming expertise in Python and C++, with experience developing real-time robotic and AI systems. Experience in deep learning and computer vision, including
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reasoning, perception–language grounding, and decision-making in robotic systems. The engineer will interface VLMs with navigation, mapping, and control pipelines to support end-to-end system experimentation
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» OtherEducation LevelPhD or equivalent Skills/Qualifications Who you are PhD in Computer Science, Machine Learning or related field or 5+ years of relevant industrial experience. Strong track record of developing
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, and a PhD research program with over 120 students. 40 academic staff conduct experimental research in many areas of Psychology, including behavioural and cognitive neuroscience, perception, learning
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capable of understanding, learning, and acting in complex, dynamic settings. The lab’s work lies at the intersection of computer vision, multimodal learning, and robotics, advancing next-generation embodied
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foundational knowledge in signal processing and machine learning. Working knowledge of computer vision and deep learning concepts, including object detection and image-based classification, with hands
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they are mainly based on predetermined rules of behavior chosen by the designer. More recently, methods derived from machine learning provided impressive results. However most are datadriven, meaning
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to provided specifications and learning objectives. Perform quality checks on uploaded content to ensure accuracy, formatting consistency, and alignment with educational standards. Create and edit generative AI
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behavior. • Year 2: investigation of modeling strategies for early perception, including spiking architectures and attention-inspired mechanisms; comparison of different learning paradigms and temporal