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challenge meeting this requirement is the simultaneous need for low-power consumption. The main objective of the project is to develop a complete end-to-end high-performance DNN system for on-premise
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is a plus point. Applicants with a PhD in Quantum Physics are also welcome, but they should have a focus on Quantum Circuits, Quantum Algorithms, and preferably expertise in developing Software
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methodology will involve the development of mathematical models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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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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learning, and AI-driven manipulation. This position offers the opportunity to work on real-world robotic systems and develop novel algorithms at the intersection of robot learning, control, and AI
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" (Supervisor: Prof Timothy O'Leary) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic
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an experimental cryo-EM laboratory (Prof. Danny Hsu’s group, Academia Sinica, Taiwan), the postdoc will: i. develop and test fitting algorithms on fully synthetic cryo-EM maps generated from simulations, ii
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computing to develop a continuous and local alternative to existing gradient-based learning rules, bridging theories of predictive coding with event-based control/ Simulate models of the learning algorithm
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comprises four faculty (Profs. Chang, Konigsberg, Korytov, and Takahashi), five postdocs, five graduate students, and a group of engineers and technical personnel — making us one of the largest U.S