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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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. The focus will be on developing algorithms and techniques that optimize beamforming performance to enhance signal acquisition, tracking robustness, and interference mitigation. Benefits Our commitment
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and financial planning tools; this includes modeling new algorithms, creating functional specifications, and testing and/or validating new financial planning tools. Collaborate with other members
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that engender trust and espouse the values of fairness, safety, and privacy in digital technologies. Key Responsibilities: Conduct research into trust technologies testing – translating research algorithms, and
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this short-term project we will use active learning to accelerate the training of deep learning algorithm to optimize 2D material Van der Waals structure discovery. Main Tasks and responsibilities: The person
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: Writing, debugging, optimizing and testing of source code with an emphasis on audio applications. Maintenance and improvement of existing audio algorithm code base including noise reduction, acoustic echo
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Responsibilities: Identify the weakness of existing watermarking and adversarial protection methods Develop new deep learning algorithms or improve existing algorithms to address the weaknesses. Prepare codes and
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intelligence and machine learning technologies/algorithms Background in software engineering and programming languages, data analysis and BI tools Proven experience in technical project and service management
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active research interests in quantum computing, quantum algorithm/software development and applications in decarbonisation who can take full advantage of the unique opportunities the QDA provides
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at an accelerated pace ? radically affecting our homes, workplaces, streets, and neighborhoods. Often, the effects of these transformations are hidden from clear view, occurring in the black box of the algorithm