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Responsibilities: To perform pioneer research in scent digitalization and computation. To further develop machine learning tasks for scent signal classification/fusion. Set up and analyze experiments under different
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. The position is for one year, renewable subject to satisfactory performance. Successful candidates will conduct research and develop advanced deep learning and computer vision algorithms. Candidates are expected
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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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research in computer vision and machine learning. To produce research reports and/or publications as required by the funding body or for dissemination to the wider academic community. To provide guidance and
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enough data for machine learning. Key Responsibilities: Learn and understand the experimental system Conduct the simulations and resolve issues Generate data using the simulations Collaborate with other
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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
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privacy-preserving algorithms to machine learning models. Analyse and interpret findings, ensuring scientific rigour and practical relevance. Prepare and submit manuscripts to leading conferences and
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Bachelor degree in Computer Science/Engineering or equivalence More than 2 papers published at top AI/Machine learning conferences Experience of deep learning and machine learning Good communication and
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leadership and expertise in the synthesis and characterization of advanced nanomaterials, specifically focusing on the integration of machine learning, wafer-scale synthesis of materials, and high-throughput
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Intelligence and Data Analytics in Air Traffic Management Systems. The selected candidate will work on developing innovative machine learning models to address key challenges in the future airspace system