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machine learning conferences/journals Job Requirements: PhD in Mathematics and/or Electronics and/or Computer Science Ability to work independently and as part of a team with strong initiatives Good
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) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices based on quantum phenomena
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, engineering, finance, and health. Key Responsibilities: To perform the pioneer research in AI for climate transformation. To further develop data-driven and machine learning tasks for fighting climate changes
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Requirements: A PhD degree in mathematics or related areas, with a strong background in topological data analysis (TDA) and machine learning on biomolecular data Proficiency in programming languages such as
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for Quantum Technologies (CQT) The Centre for Quantum Technologies (CQT) in Singapore brings together physicists, computer scientists and engineers to do basic research on quantum physics and to build devices
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Information Engineering and Media to develop Machine Learning and AI algorithms for real-world and media-related applications. The Research Associate/Research Fellow is also expected to support teaching
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languages; A good record of publications in reputable peer-reviewed journals or conferences in maritime transport, logistics management, machine learning, deep learning, and optimization; Proficient in
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Responsibilities: Conduct programming and software development for graph data management. Design and implement machine learning models for optimizing graph data management. Conduct experiments and evaluations
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conditions. The researcher will also work with team members within the consortium in generating necessary data required for developing a machine learning model for storm surge prediction. Key Responsibilities
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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