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reconfiguration operation. Develop and evaluate fast and efficient scheduling algorithms for fast control and reconfiguration of the optical AI compute clusters. Realize a small-scale compute cluster lab testbed
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systems, or continuous-time and discrete-time LTI systems theory is a plus. Experience with mathematical modeling, optimization, numerical computation, algorithm development, or machine learning. Prior
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on this project, you will: develop mathematical theory for non-linear inverse problems governed by wave equations; design and analyse numerical algorithms for inverse problems, uncertainty
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algorithms on a four qubit quantum processor, realized baseband control of single spins, and demonstrated entanglement between remote spin qubit registers using spin shuttling. As a PhD researcher, you will
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to accurate sample reconstructions using advanced signal processing and tomographic reconstruction algorithms. With the inclusion of noise the object estimation accuracy will be based on statistical concepts
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, you will focus on developing mathematical models and numerical algorithms that systematically integrate uncertainties into the design process of optical systems. The goal is to enable novel design
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worlds. You will design QEC codes suited to realistic hardware, develop the decoding algorithms that make them practical, and map the trade-offs between reliability, qubit overhead and decoding latency. A
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of repeatedly solving wave equations. In the project, we will develop a new mathematical and computational framework that combines PDE-based modelling with ideas from data-driven reduced-order modelling. The aim
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Python and/or C++. Experience with scientific software development is an advantage. An interest in quantum algorithms and the motivation to contribute to one of the world’s emerging research areas. Strong
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expertise in artificial intelligence, computer vision, human-computer interaction, and psychology. Its technical core lies in developing robust and adaptive visual speech recognition models. Close