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of novel edge-assisted computation offloading strategies that leverages edge intelligence. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development. The core
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discrete choice modelling, behavioural data science or machine learning? Are you interested in developing the next generation of AI tools that accelerate scientific discovery while maintaining behavioural
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and computer scientists from both Nottingham Trent University (NTU) and the University of Nottingham (UoN). The successful candidate will contribute to a work package focused on the development of a
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. The Role Faculty of Environment, Science and Economy The successful applicant will contribute to the project NATALIE by developing AI algorithms that integrate data from various sources to better understand
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measurements and collaboration with related valve disease projects. • IDIBAPS, Spain (2 months): access to clinical datasets and validation of developed algorithms against clinical and in-silico data. About You
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learning algorithms. Collaborating with industry partners to understand operational requirements and developing AI pipelines for analysing visual and sensor data collected during inspection processes
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-oriented validation experiments, and analyze the resulting data rigorously. Develop, implement, and optimize signal and image processing algorithms using appropriate programming environments and
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. The role will bridge rigorous theoretical work with hands-on offloading algorithm design and development. The core responsibility is to build and validate these offloading strategies, complete with Python
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lead the design, statistical optimisation and validation of assays for clinically relevant bladder cancer targets. Their central objective will be to develop an algorithmic workflow to detect new target
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algorithms for automated driving. You could also develop your own research portfolio by supervising MSc individual research projects aligned with the Centre’s research themes. You will be expected