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learning architectures, such as PyTorch, TensorFlow, etc. Proficiency of programming skill with quantum machine learning architectures, such as PennyLane, Qiskit, and similar platforms, is preferred. Capable
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the area of Cloud Media Computing, Content Delivery Networks, Data Center architecture, and Big Data analytics. We are seeking 1 motivated Senior Research Fellow in the topic of “Digital Twin for Advanced
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the area of Cloud Media Computing, Content Delivery Networks, Data Center architecture, and Big Data analytics. We are seeking for 1 motivated Research Fellow in the topic of “Digital Twin for Advanced
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experts in architecture, urban design and planning, social sciences, public health, medicine, transportation, technology, and urban economics. We are seeking a highly motivated and talented Research Fellow
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implement multimodal LLM architectures that integrate vision, language, and action for embodied AI systems. Develop and optimize deep learning algorithms to enable robotic arms to perform complex tasks guided
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to work on Liaise with co-I from NetaTech and Tohoku University to apply the in-house developed light conversion film on the architectural design and system used for the UmFm. Taking care of the day to day
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programming skill with quantum machine learning architectures, such as PennyLane, Qiskit, and similar platforms, is preferred. Capable of handling multiple tasks across projects and research activities. Showing
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generative AI is preferred. Knowledge of programming skill with deep learning architectures, such as PyTorch, TensorFlow, etc. Capable of handling multiple tasks across projects and research activities
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top conferences/journals, such as CVPR, NeurIPS, AAAI, IJCAI, T-PAMI, IJCV, and etc. Experience in generative AI is preferred. Knowledge of programming skill with deep learning architectures, such as
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been pursuing novel research in parallel algorithms with strong theoretical underpinnings, for the Compute Unified Device Architecture (CUDA) enabled NVIDIA GPUs, to solve large-scale Assignment Problems