495 algorithm-"Multiple"-"U"-"Simons-Foundation"-"Prof"-"UNIVERSITY-OF-SOUTHAMPTON" positions in Singapore
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optimization problems Develop mathematical modeling framework to find the optimal operation strategy Conduct computer programming to verify the efficiency of the designed solution algorithms Analyze data
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researcher in natural language processing and large language models to work with a team from multiple disciplines of machine learning and artificial intelligence to develop multimodal large language models
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; Develop models and algorithms for energy-aware scheduling, workload prediction, and performance–energy trade-off optimization; Investigate network system energy efficiency, including traffic scheduling
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, including Computational Fluid Dynamics (CFD) for thermal analysis and energy simulation for consumption modelling. Design, train, and implement advanced machine learning and deep learning algorithms
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on novel agent architectures, including tool-use methodologies, advanced planning algorithms, and multi-agent collaboration for simulation-based optimization. Innovate & Conceptualize: Design and
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edge-assisted offloading strategies for IoT networks. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development for IoT networks. The core responsibility is
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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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Responsibilities: Conduct individual research within the designed project: process data, develop research methods, build and evaluate computer vision and machine learning algorithms empirically. Author research
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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EmoRoom (Emotion + Classroom), an interactive visual analytics system to analyze and summarize student emotions from classroom videos, using emotion recognition algorithms and intuitive visualizations