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. The role will focus on developing machine learning and mathematical optimization solutions for electric vehicle fleet charging optimization under different constraints. Key Responsibilities: Formulate
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at the School of Physical & Mathematical Sciences, Nanyang Technological University (NTU). The candidate is expected to work on the cryptography and/or machine learning. Key Responsibilities: The candidate will
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: Research activities related to Quantum Machine Learning, Agents and Information Theory Job Requirements: For the Research Fellow position, the candidate must hold a Ph.D. degree in quantum information
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topics ranging across programming language (especially Bayesian statistical probabilistic programming), statistical machine learning, generative AI, and AI Safety. Key Responsibilities: Manage own academic
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geophysical investigation, data analytics, and machine learning. Key Responsibilities: The Project Officer should be familiar with geophysical investigation, data analytics, and machine learning. The Project
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candidates will be involved in a project that is related to generative design. Key Responsibilities: To independently undertake research in computer vision and machine learning. To produce research reports and
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novel research methodologies in computer vision, deep learning architectures, and neuro-fuzzy systems to contribute to the development of robust AI frameworks for medical diagnosis and treatment support
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candidates will be involved in a project that is related to generative design. Key Responsibilities: To independently undertake research in machine learning. To publish high-quality research papers as required
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, Computer Science, Electronics Engineering or equivalent. Experience in one or more of the following areas: machine learning, deep learning, software-hardware co-design, computer system performance, design
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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