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Field
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development skills Model deployment (e.g., ONNX, TensorRT) Edge computing or embedded vision systems (e.g., NVIDIA Jetson Nano) Real-time processing and GPU acceleration Experience working on industry R&D
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embedded AI systems. They will demonstrate a strong track record of high-quality research in machine learning/AI and/or embedded systems, evidenced by publications in leading conferences and journals
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Queen’s Communities and Place (QCAP) is an AHSS Faculty flagship research initiative based in the School of Social Sciences, Education and Social Work. It launched in November 2021, and supports
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& Population Oncology Department, a vibrant and multidisciplinary environment that fosters cutting-edge research and world-class clinical training. The post will be embedded within the Systems Cancer Immunology
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an exciting opportunity to contribute to a high-impact, mixed-methods study that champions inclusive, ethical and co-produced research with people living with dementia and their carers. You will work
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experience Proven experience with sensor integration, data acquisition systems, and embedded hardware prototyping, preferably in aquatic or environmental monitoring contexts. Strong understanding of real-time
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Engineering, Robotics, or related fields. Strong experience in UAV hardware design, embedded systems, and real-world flight testing. Proficient in multi-agent system integration and middleware (e.g., ROS 2, PX4
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The London School of Hygiene & Tropical Medicine (LSHTM) is one of the world’s leading public health universities. Our mission is to improve health and health equity in the UK and worldwide; working
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The London School of Hygiene & Tropical Medicine (LSHTM) is one of the world’s leading public health universities. Our mission is to improve health and health equity in the UK and worldwide; working
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the development and translation of rehabilitation technologies is strongly preferred. Prior experience with embedded systems or biomechanical evaluation in wearable devices is desired. Special Instructions Contact