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focused on the challenge of accelerating ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track
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ternary neural networks using FPGA devices. The successful candidate will have significant experience in machine learning, FPGA design and an outstanding track record in conducting machine learning research
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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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effectively with a range of stakeholders. Experience working with a range of computer systems and applications, including microwave/microelectronics and low-level software languages such as C/C++ and/or FPGA
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multilayer PCB, FPGA programming, embedded systems, and preferably ASIC-design. Knowledge in Systems Engineering, particularly in Space and Defence is highly regarded. You will also demonstrate personal
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level of experience working with a range of computer systems and applications, including microwave/microelectronics and low-level software languages such as C/C++ and/or FPGA hardware design languages