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Responsibilities: Conduct research on the design and analysis of scalable machine learning systems using convex/nonconvex optimization and federated learning methods. Develop algorithms and prototypes
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., Azure AI, OpenAI, Google Cloud AI). Participate in code reviews, solution architecture discussions, and deployment planning. Monitor and optimize workflow performance and user experience. Maintain
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areas: Data Science and Optimization Computational Mathematics and Scientific Computing Quantitative Finance Analysis Geometry and Topology Combinatorics and Discrete Mathematics The review process will
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serve as a strategic legal advisor, driving excellence in legal and compliance frameworks while fostering innovation, partnerships and optimization. This role requires a seasoned legal professional with
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writing/presentation Job Requirements PhD degree in an engineering field related to this project Experience in dynamic modeling, machine learning and optimization & controls Having basic knowledge in carbon
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engineering strategies to enhance production yields of target chemicals. Conduct lab-scale fermentation, analytics, and process optimization. Publish research findings in high-impact journals and present
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uses. To investigate feature-level just-noticeable difference modelling for machines to facilitate assessment and optimization. To formulate a comprehensive visual feature codec for machine uses
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of projects. Job Description: The successful applicant will be responsible for Performing literature review and background study on collaborative AI Develop algorithms and system designs that can optimize
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operational policies and procedures to optimize facility usage and safety standards. Strategic Planning & Development: Plan and execute strategies to increase facility utilization and membership engagement
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framework on how to build up a generic framework to use learning-assisted approach to solve various optimization problems Develop mathematical modeling framework to find the optimal operation strategy Conduct