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Field
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Engineering, or related field. At least 3 years of relevant experience in computer vision, artificial intelligence, etc. Proficiency in programming languages such as C and Python Proficiency in deep learning
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University focused on advancing computer vision, multimodal AI, generative AI, and embodied AI. Founded in 2018, the lab has grown into a vibrant research group with around 40 members comprising faculty
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should demonstrate strong expertise in robotic systems, with experience in one or more of the following areas: robot perception, 3D machine vision, object pose estimation/tracking, vision-guided
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, or similar. Solid expertise in computer vision techniques, transformer architectures, and multi-modal learning. Familiarity with reinforcement learning (RL) principles, curriculum learning strategies, and the
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: PhD in Computer Science or relevant fields; Strong background in machine learning and computer vision. Prior experience in 3D vision is preferable. Strong publication records in top-tier machine
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research. Job Requirements: PhD in Computer Science or relevant fields; Strong background in machine learning and computer vision. Prior experience in 3D vision is preferable. Strong publication records in
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(Kubernetes), serverless computing, and REST API development. Proficient in Python, with basic experience in machine learning or computer vision libraries; familiarity with Vision-Language Models (e.g., CLIP
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, and construction progress analysis. Key Responsibilities: Conduct research in computer vision, machine learning, large language models, AI agents, and 3D reconstruction for infrastructure digitalization
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). Hands-on experience with game AI agents and/or GUI agents such as Mineflayer, Unity ML-Agents, or similar. Solid expertise in computer vision techniques, transformer architectures, and multi-modal
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) as Art Historical Tool Network Analysis and Cultural Data Human–AI Collaboration in Art Historical Interpretation Digital Provenance Research and Collection Histories Computer Vision for Art Historical