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building a UAV capable of quantifying aerosol size, composition and radiative effects in the Upper Troposphere-Lower Stratosphere (UTLS). Lead the selection, integration, and testing of advanced sensors
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methods for on-sensor computer vision. Specifically, the job involves developing algorithms for embedded systems that are designed to produce sensing and computation on the image plane, and on understanding
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(SDR) platforms and characterise them in the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience
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Bay. The key responsibilities of this role include; Using a combination of automated algorithms and manual data processing to identify bottlenose dolphin signature whistles in a multi-year acoustic
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are not limited to: network architecture design for NTN and terrestrial network (TN) convergence, intelligent traffic steering algorithms between TN and NTN, orchestration of TN/NTN resources for end-to-end
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of energy-efficient hardware, embedded machine learning and sensor-integrated nodes for the edge of the network. We offer a supportive and inclusive academic environment, with access to state-of-the-art lab
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(SDR) platforms and characterise them in the presence of interference in a variety of spectrum sharing scenarios, seeking opportunities for algorithms which provide enhanced interference resilience
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that is pioneering transformative edge computing solutions including novel semiconductor devices, design and implementation of energy-efficient hardware, embedded machine learning and sensor-integrated
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enable the development and operation of new algorithms and software to solve leading-edge research problems. You will find this work exciting if you: Want to help build and maintain some of the largest