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Fellow in applied adversarial machine learning. This exciting opportunity will contribute to the D-XPERT (AI-Based Recommender System for Smart Energy Saving) project. The D-XPERT project represents a
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skills in realist methodology and excellent project management to lead this review. They will also need to be able to engage in deep critical thinking to develop theoretical insights, have excellent verbal
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new privacy enhancing technologies, privacy sensitive machine learning to personalise automatic online safety responses and immersive simulation environments to explore how safety and can be compromised
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will be to develop generative machine learning models and signal processing algorithms for sound generation, given prompts from text and/or video. This work is built on the recent contributions of CVSSP
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devices, circuits and applications. The work builds on the ALPACA - A new low-complexity paradigm for analogue computation and hardware learning research project, awarded as a prestigious EPSRC Fellowship
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. This project will be based in the School of Chemistry and Chemical Engineering, Faculty of Engineering and physical sciences. We are committed to achieving equality for all those who learn and work here and
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greener carbon sources. This will ultimately enable us to learn how to rationally design of strains for greener manufacturing and make this strategy broadly applicable to other industrial Streptomyces