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MACQUARIE UNIVERSITY - SYDNEY AUSTRALIA | North Ryde, New South Wales | Australia | about 1 month ago
differential geometry, algebraic geometry, etc.) or for computer science (such as machine learning, linear logic, etc.).While the position start date is flexible, the successful applicant must have completed
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differential geometry, algebraic geometry, etc.) or for computer science (such as machine learning, linear logic, etc.). While the position start date is flexible, the successful applicant must have completed
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, laying the foundations of next generation machine learning. We do this by combining the mathematical and computational cultures, and the methodologies and theories, of statistics, logic, language
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standards. Language & Comprehensive Ability Fluent in academic English writing and oral communication, capable of independently conducting international academic research. Strong logical thinking, independent
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semantic heterogeneity—differences in terminology, structure, and logic—remains a central barrier to reusability, interoperability, and reproducibility. This postdoctoral position addresses a fundamental and
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total). Support the Informal Logic editorial team and copy-editing team. Develop a special issue policy and a social media strategy for Informal Logic, to be presented to and discussed with the editorial
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of science-based data collection activities (qualitative and quantitative) and data analysis. Strong science communication skills, both written and oral. Experience in logic modeling, strategic planning
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and academic researchers. Responsibilities will involve: 1. Research & Development a. Lead System-Technology Co-Optimization (STCO) research on BS-PDN for advanced logic, chiplet-based, and 3DIC
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, laying the foundations of next generation machine learning. We do this by combining the mathematical and computational cultures, and the methodologies and theories, of statistics, logic, language
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a. Conduct cutting-edge research on BS-PDN for advanced logic, chiplet-based, and 3DIC systems. b. Develop novel design methodologies, modeling approaches, and optimization techniques for BS-PDN