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enabler for surgical treatments. The role will primarily involve construction and evaluation of hardware, data collection, data analysis and writing scientific papers/reports. In addition, there will be
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. The role includes supporting the hardware and software infrastructure required to acquire high-quality health data, ensuring system reliability, and advising on improvements through the integration of novel
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. The second position will be offered to a candidate with a desire to implement deep learning algorithms on clinical hardware (either developing new imaging hardware or implementing deep learning approaches
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approaches in radiation therapy. The second position will be offered to a candidate with a desire to implement deep learning algorithms on clinical hardware (either developing new imaging hardware
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research outcomes, provide expert advice, and exercise sound judgement in addressing the challenge of hybrid microwave-optical quantum hardware using rare-earth ions in solids. The School of Physics is
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and/or hardware testing environment to compare and evaluate the proposed techniques. Disseminating results through scientific publications and conferences The candidates are expected to actively
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, including neural networks hardware accelerator systems. • Design, model, and simulate memristor cells and circuits tailored for AI acceleration. • Collaborate on the fabrication and experimental
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on energy-efficient circuit design and software-hardware co-optimization, with exciting applications in graph-based prediction. What we’re looking for: A PhD in Electrical and Computer Engineering or a
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algorithms for parallel/distributed AI/ML Hardware-aware and resource-efficient partitioning for parallel/distributed AI/ML Optimization of process-to-process communication in parallel/distributed AI/ML
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and to accelerator design. This is expected to be a supplementary element with a primary focus on hardware system development. Proposals should also highlight their contribution to priority areas