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Field
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, post-docs and interns collaborating across universities to build better algorithms, software tools and benchmarks to assess the safety of AI implementations at the software and hardware level. We
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. The task of the theory group led by Prof Kyriienko at the University of Sheffield within the consortium is to lead nationally the development of quantum machine learning (QML) algorithms. The research will
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for application to fusion reactors, considering factors such as muon flux, detector sensitivity, and data analysis algorithms. PhD candidates will be tasked with developing simulations of complete detectors and
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apps and software algorithms would be desirable, as would an understanding of major depression and its pharmacological treatments. Diversity Committed to equality and valuing diversity Our active
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, anomaly detection, cybersecurity, or distributed AI systems. We welcome candidates with experience in edge data pipelines, sensor data processing, and AI-based forecasting or classification. We particularly
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(numerical model will be based on commercial package COMSOL) simulations of multi-modal sound propagation in pipes with elastic walls and in presence of defects Develop acoustic sensor based on the state
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Job title: Assistant Professor in Signal and Image Processing or Robotics School: School of Engineering & Physical Sciences Institute: Institute of Sensors, Signal and Systems Grade and Salary
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mix of algorithm engineering and formal methods, alongside more traditional software engineering activities. This project involves developing software which is both mathematically rigorous, and
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This post is funded by the ‘Integrating quantum sensors with bespoke quantum error correction’ project supported by the Engineering and Physical Sciences Research Council (EPSRC). The task
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distributions from process-induced microstructure variations using the surrogate models created. Work with the extended team to link the simulation of sensor data with new multi-scale processes for microstructure