1,803 algorithm-development-"Prof"-"Washington-University-in-St"-"Prof"-"Prof" positions in Singapore
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: DRivers, Enablers and pathways of Adolescent developMent in Singapore (DREAMS): The Singapore Longitudinal Cohort Study (SG-LCS) Phase 1 – Project 7 Project Introduction: This study seeks primarily
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Learning (e.g., DDPG, PPO, MARL). NLP including language understanding, generation, explainability and reasoning, and dialogue systems. Develop and evaluate AI models, including: Agent-based and LLM-based
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algorithms Evaluate performance, interoperability, and security implications of replacing classical cryptographic schemes with quantum-safe alternatives Support the development of technical documentation
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, such as data storage, budgets, expenses, assets, and ethics approvals. Key Responsibilities: Design and implement research, including statistical models and algorithms to extract insights from data Develop
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NUS Researchers and NUS Staff; Develop first-generation prototypes of systems and data endpoints through which NUS Researchers and Staff can access and use the NUS Data products; and Promote improved
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that are relevant to industry demands while working on research projects in SIT. The primary responsibility of this role is to lead the research and development of a secure and privacy-preserving multimodal biometric
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Responsibilities: Designing and developing scalable algorithms for building Data+AI systems. Writing research papers of high quality based on research results Building deployable Data+AI systems based
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ethical and security standards. Concept and Algorithm Development: Innovate in data science, machine learning, and AI. Data Analysis and Reporting: Contribute to data analysis, reporting, and publication
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to contributions in top-tier international journals and real-world implementations. Responsibilities: Develop and refine algorithms for decision optimization and risk control, utilizing big data and advanced
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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