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Field
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topics. Candidates should have some experience working with FPGAs as well as an understanding of computer networks. Experience with both RTL and HLS design is favoured. The ideal candidate would have some
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signal processing, and FPGA readout systems. Teach undergraduate and graduate courses related to semiconductor devices, analog electronics, signal processing, and FPGA-based systems. Mentored graduate
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Reconfigurable/Spatial computing architectures, such as FPGAs, CGRAs, and AI accelerators, offer significant opportunities for improving performance and energy efficiency compared to traditional CPUs
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on hardware which may include CPUs, GPUs and FPGAs. In particular we are interested in applicants who have experience of modern coding practices and software techniques. The post-holder will work with Prof. Ben
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parallel processing, FPGA coding and analysis, along with Machine Learning and AI based image analysis. The final aim of the project will be to generate in-situ / live film profile data to coating line
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. Familiarity and understanding of microwave and RF measurement circuit elements and instruments Familiarity with Field Programmable Gate Array (FPGA) operation and coding Skills Needed: Knowledge, understanding
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Neuromorphic and AI-Optimized Processors – Design AI-specific chip architectures, including neuromorphic and domain-specific accelerators (TPUs, NPUs, FPGAs), for low-power and real-time AI processing. AI-Driven
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processing techniques using field-programmable gate arrays (FPGAs), alongside analog and digital circuit design. This research underpins biomedical applications, with a particular focus on early melanoma
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hardware design (Verilog/VHDL), FPGA-based acceleration, etc. Experience with deep learning frameworks like PyTorch, Keras, or TensorFlow, and tools such as Jupyter Notebook, is expected. A strong foundation
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signal processing algorithms on FPGA, optimized to significantly improve the resolution of real-time energy measurements made by the ATLAS Liquid Argon Calorimeter system. Use novel high-level synthesis