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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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. Write the report for the project progress. Work with research assistant for the prototype. Job Requirements: PhD in Electrical and Electronic Engineering, Computer Engineering / Science, or related field
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to prospective fellows whose ambition is to pursue an academic career - the program is tailored to facilitate such careers. In addition to mentoring in the specific areas of specialization, the CIL Postdoctoral
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expected, and familiarity with modern machine learning methods will be considered an asset. NUS offers a vibrant research environment, with access to high-performance computing facilities and opportunities
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expansion of its programme on international environmental law with an emphasis on climate change law and policy. The objective of the position is to engage in research on emerging issues related
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manufacturing, mechatronics, innovative design, nanotechnology, and biomedical and computational applications. Key Responsibilities: The research fellow will be leading the development of AI-based decision-making
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Responsibilities Designing and managing a programme of research to meet agreed objectives. Working closely with experimental and data scientists in the group to ensure the progress of the project. Oversee
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Responsibilities Designing and managing a programme of research to meet agreed objectives. Working closely with experimental and data scientists in the group to ensure the progress of the project. Oversee
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Responsibilities Designing and managing a programme of research to meet agreed objectives. Working closely with experimental and data scientists in the group to ensure the progress of the project. Oversee
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2025. Duties • Fellows will develop and implement a coherent specimen-based research programme that will advance knowledge and understanding one or more groups of tropical Southeast Asian terrestrial