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synthesis tools (ASIC, FPGA). Good programming and scripting skills. Excellent English communication, presentation, and writing skills. Must be a team player. Knowledge of computing-in-memory is an added
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design and synthesis tools (ASIC, FPGA). Good programming and scripting skills. Excellent English communication, presentation, and writing skills. Must be a team player. Knowledge of computing-in-memory is
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. Experience with algorithm design, embedded DSP development, multithreaded programming, GPU development, SDR hardware platforms, FPGA development, and/or Linux-based designed tools is desired. Representative
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making a difference to people's lives. We believe that inspiring our people to do outstanding things at Durham enables Durham people to do outstanding things in the world. Being a part of Durham is about
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energy-efficient CMOS blocks implementing SSM-based LLMs. Prototype hardware blocks on FPGA and prepare for ASIC tape-out. Benchmark performance and comparison with transformer accelerators. Work with
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and run it efficiently on different hardware architectures. For example, Google has built TensorFlow, a framework for deep learning allowing users to run deep learning on multiple hardware architectures
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of neuromorphic systems for different types of onboard sensing and processing tasks in the space environment. Your research will be guided by your own expert judgement and insight into current trends in AI hardware
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activities, which span a diverse range of advanced electronic systems. These include FPGA and neuromorphic computing, edge AI, machine learning, sensing technologies, and energy harvesting—key components