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, Python, Robot Operating System) is required. The position is open to PhDs with backgrounds in AI, and/or computer vision and robotics/controls, and with less than 5 years of experience after receiving
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learning and data analysis. Familiarity with one or more of the following areas: artificial intelligence, natural language processing, computer vision, multimodal learning, affective computing, human-robot
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collaborators. Requirements: Applicants should have a PhD in Computer Engineering, Computer Science, or a related field. Extensive and sound knowledge of ML, AI, DNN, LLMs/VLMs, Multimodal LLMs, RAG, Agentic
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workflows in complex organizational settings. Qualifications: Applicants must have a PhD in Computer Science or related field, with no more than five years post receipt of the PhD. Experience in one or more
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Deadline 29 Aug 2026 - 00:00 (UTC) Country United Arab Emirates Type of Contract Permanent Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is
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learning and data analysis. Familiarity with one or more of the following areas: artificial intelligence, natural language processing, computer vision, multimodal learning, affective computing, human-robot
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collaborators. Requirements: Applicants should have a PhD in Computer Engineering, Computer Science, or a related field. Extensive and sound knowledge of ML, AI, DNN, LLMs/VLMs, Multimodal LLMs, RAG, Agentic
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, and cognitive systems and intelligent vision systems, including efficient learning and inference of complex AI/ML algorithms, specialized neural processing hardware and design tools, and ML security
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to areas such as deep learning, natural language processing, computer vision, reinforcement learning, ethical/trustworthy AI, and interdisciplinary applications of AI/ML in various domains. We welcome
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: artificial intelligence, natural language processing, computer vision, multimodal learning, affective computing, human-robot interaction, social robotics, or human-centered AI. Experience with machine learning