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Field
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of Technology and QuTech. The goal is to further develop fault-tolerant architectures for photonic platforms based on fusion-based and measurement-based computation, addressing photon loss and other hardware
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test center for non-nuclear testing of reactor and turbine systems is under construction, giving SAINT researchers hands-on access to hardware validation at a scale rarely available in academic maritime
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large datasets and developing experimental techniques, including the use of artificial intelligence. There are also opportunities to be involved in the development and testing of new hardware for the next
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problem. Do a theoretical analysis of the assigned problem using tools from information theory and related fields. Design a solution which is implementable on a computer and in hardware. Collaborate with
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fields. Design a solution which is implementable on a computer and in hardware. Collaborate with colleagues to implement the solution in hardware at the ACES lab at the Institute of Theoretical
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. The success of neural networks as a platform for developing AI is partially explained by the fact that backpropagation, the primary algorithm used to train them, runs efficiently on conventional CMOS hardware
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SD-26109- POSTDOCTORAL RESEARCHER IN AI-BASED ENERGY MANAGEMENT OF RESILIENT MICROGRIDS WITH SECO...
simulation models of microgrids, second-life battery systems, solar PV generation and critical community loads. Validating the proposed control strategies using real-time simulation and hardware-in-the-loop
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designing and building hardware solutions, e.g. using Arduino, Raspberry Pi, 3D-printing, CAD and CNC machining and/or laser cutting Language Requirements: Excellent command of English (C1), both orally and
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addresses that challenge by developing a multimodal sensing and inference framework that can run on compact AI edge hardware while remaining reliable in complex, contested, or visually degraded environments
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are continuously subject to "domain shifts" caused by fluctuating conditions, hardware degradation, or changing physical surroundings. Traditional AI models are often brittle under these distribution shifts, leading