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Details Title Postdoctoral Fellow in Riemannian Optimization School Harvard John A. Paulson School of Engineering and Applied Sciences Department/Area Position Description A postdoctoral position is
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of advanced technologies. This includes developing cutting-edge AI/ML models and datasets; learning how to take advantage of unparalleled computing resources in the academic environment by optimizing AI/ML
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to, the following: Data Analysis and Programming Develop study questions and analytic approach (including literature searches and data searches using various sources) Optimize, test, and debug model code Clearly
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. Research areas include Representation Learning, Machine learning and Optimization on graphs and manifolds, as well as applications of geometric methods in the Sciences. This is a one-year position with
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questions and analytic approach (including literature searches and data searches using various sources) Optimize, test, and debug model code Clearly document model development, structure, logic, coding
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?s Comms. writing team to effectively synthesize content across platforms Publish, maintain, and update the Alumni section of the HKS website, including making recommendations and driving optimization
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formats and spaces. Manually set up A/V systems for staff meetings and special events. Work with faculty to determine optimal technology integration in classroom settings and provide walkthroughs
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of unparalleled computing resources in the academic environment by optimizing AI/ML models including scaling models across a large set of GPUs; building or optimizing LLMs to tackle new, complex tasks; developing
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, workplace safety, OSHA, ADA requirements, etc.). Partners with others across Campus Services groups, customers, and the University community at large to achieve optimal delivery of E&U services and efficient
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and infrastructure for GenAI products, including search interfaces, chatbots, and text summarizers, ensuring optimized performance that meets specific product goals. Collaborate closely with product