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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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control using deep learning. Implement and test new algorithms in actual robot platforms. Job Requirements: PhD in Electrical and Electronic Engineering or related field. Hands on research experiences in
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). 3. Proficiency in at least one mainstream deep learning framework (PyTorch or JAX) 4. Ability to independently design and execute research projects, with a track record of high-quality publications. 5
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in signal representation/processing, esp for scent signals. Prior research experience and track record in signal detection, machine learning and deep learning. Prior programming experience in state
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physiology Coding proficiency (e.g., Python, R) and familiarity with deep learning tools are strong assets A strong publication record, critical thinking, and collaborative mindset Application Instructions
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Engineering, Automation, Mechanical Engineering, Control Engineering, Mechatronics, Computer Science, AI, etc. Strong background in autonomous driving, deep learning, interaction modelling, prediction, robotics
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: Proficiency in Python and major deep learning frameworks such as PyTorch or TensorFlow Familiarity with transformer architectures and large language models (e.g., BERT, GPT) Experience in building, training
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programming languages such as C and Python Proficiency in deep learning frameworks such as Pytorch and Tensorflow Knowledge in imaging and computing device and equipment Good written and oral
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optimization of multi-modal LLMs. Investigate and implement methodologies to ensure AI authenticity, accountability, and the integrity of digital content. Develop and refine machine learning and deep learning
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, and innovators to thrive in the digital age. Located in the heart of Asia, NTU’s College of Computing and Data Science is an ‘exciting place to learn and grow'. We welcome you to join our community