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. Experience with embedded systems and hardware/software integration in a research or prototyping context. Experience with FPGA/RTL development and Xilinx tools, and CUDA coding for GPU acceleration. Knowledge
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systems, FPGA/RTL, and RF technologies, and CUDA coding for GPU acceleration is a plus. Strong leadership, communication, and documentation skills.
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bridging (e.g., JESD204C/eCPRI), and CUDA coding for GPU acceleration. Knowledge of RF calibration, test automation, and signal integrity in a research or prototyping context. Track record of peer-reviewed
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of computational resources (e.g., GPU servers and related infrastructure). Contributing to student and industry project work, including data preparation, modelling, evaluation, and deployment-related tasks where
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experiences on computer vision • Strong programming skills in using Deep Learning tools like PyTorch and GPU clusters. • Good written and verbal communications. • Open to Fixed Term Contract
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RFSoC platforms, and CUDA coding for GPU acceleration.
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electromagnetic engineering problems. Programming experience in C/C++ and GPU is desired. Other qualifications being expected are as follows. Good analytical and problem-solving skills; Good analytical and
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infrastructure--- including GPU-enable units and HPC server Manuscript and grant preparations --- for all research pertaining to mental health NLP and behavioral work. And to support grant administration, co
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expertise in optimisation; Computer Science, with expertise in design and analysis of algorithms and high-performance (GPU) computing; Industrial and Systems Engineering, with AI in process mapping and Conops
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topics related to the position. Experience with data management, HPC and GPU is a plus. They should also demonstrate the ability to work effectively in a multicultural, interdisciplinary team at EOS and