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-critical systems. The research will focus on developing AI-powered verification tools, health monitoring algorithms, and compliance assurance techniques that ensure system reliability throughout
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as to what role law should play in reducing potential harms, in helping to distribute risks and benefits across different groups in society, and in how existing (or future) legal rights and duties
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of large-scale robot systems (ground and aerial). The ideal candidate will possess hands-on experience with designing and implementing reinforcement learning algorithms, and deploying them onto real robots
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Engineering or a related field. In this role, the selected candidate will be responsible for designing, developing, and optimising algorithms for processing and analysing signals in real-time applications
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-holomorphic Hilbert Modular Forms”. The central aim of the project is to develop explicit algorithms for computing with non-holomorphic Hilbert Modular Forms and using these algorithms together with theoretical
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considered for this project. Application form Closing date 14 March 2022 Decision date May 2022 Additional information ¿Multi-criteria Automatic Algorithm Configuration under Streaming Problem Instances
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proficiency in distributed and high-performance machine learning algorithms, methods for exploiting modern system architectures for high-performance AI, and quantum distributed computing. A proven track record
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expertise in distributed and high-performance systems, you will be able to display proficiency in distributed and high-performance machine learning algorithms, methods for exploiting modern system
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AI algorithm learning when subjected to cyber attacks in Edge Computing environments. At the Edge AI Hub, you will join an internationally renowned and multi-disciplinary team co-led at Southampton Dr
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immunofluorescence imaging. The successful candidate will support the design, optimisation, and analysis of multiplex panels to characterise the spatial distribution of immune and other cells within tumour tissues