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Field
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efficiency through parallelism (time-, frequency-, and mode-multiplexing), with a specific focus on photonic reservoir computing Relate parallelism to applications, e.g., algorithmic parallelism, multi-tasking
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Relate parallelism to applications, e.g., algorithmic parallelism, multi-tasking, etc. Address nonlinear equalization in optical signal transmission and provide a comparison with neuromorphic electronics
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well as to optimize the tooling geometry. These process simulations require efficient numerical algorithms to be practical and to enable robust optimization. Therefore, in this project you will: Develop efficient
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and in-house developed software to predict structures of interacting proteins and in collaboration with the Steinegger lab, developed highly efficient AI-based algorithms to compute similarity between
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the Department of Information Technology website . At the Division of Systems and Control , we develop and analyze both theory and concrete tools to design systems that learn, reason, and act in
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related to Computer Science, Machine Learning, Data Science, Information Management or other related areas; Have skills in the development and application of machine learning models in supervised and non
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: Develop an event-driven RL algorithm that sparsely updates network state and parameters that will significantly improve energy to-solution efficiency compared to conventional digital accelerators when
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park, in a dynamic ecosystem that brings together academics and companies of all sizes. The Signal team of the i3S Laboratory (https://i3s.univ-cotedazur.fr/signal ), aims to develop advanced, innovative
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Everyone is talking about artificial intelligence. But who is developing the necessary chips? We are, for example! Would you like to help drive the development of a new highly efficient AI hardware
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potential projects: Development of modern auto-differentiation (JAX-based) physics simulators for the discovery of new physics experiments) Developing, benchmarking and advancing state-of-the-art AI-driven