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Field
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, characterisation and/or calibration of image sensors. Good understanding of, and demonstrable experience in, writing bespoke data acquisition and data analysis code and/or software algorithms with a focus on
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mobile robotics, you will manage own academic research and administrative activities, adapt existing and develop new methodologies in robotics, design working algorithms from theories, deploy and test
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in candidates who have expertise in analysing and interpreting satellite remote sensing data from Synthetic Aperture Radar (SAR) and multi/hyper-spectral sensors for measuring ground deformation
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, encryption/decryption and compression; use of microelectronics devices (including COTS); implementation, inference, verification and validation of algorithms** on processing hardware platforms for space
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with MoniRail Ltd and Durham University. The primary focus will be on designing and implementing deep learning and anomaly detection algorithms to analyse large-scale, real-world sensor data collected
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us to build/learn generative, probabilistic forward models of users and their physical and computational environments. This will involve modelling sensors, developing dynamic models for control and
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the University of Southampton, where fibre optic sensors are being developed to measure strain in real time during the cure process. As part of this exciting project, we are collaborating with our spin-out company
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applications would be particularly beneficial, although not essential. In addition, experience in artificial intelligence, cloud computing, sensor networks and/or data visualisation would also be highly
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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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aims at addressing computational challenges associated with data acquisition and information extraction from complex sensors and sensor networks. Crucially, uncertainty management and quantification