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to monitor oceanic CO2 uptake with improved confidence. Any future observational network utilises a range of instrument/sensor technologies, deployed on different platforms, and measuring multiple variables
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web technologies Experience in teaching bioinformatics Previous experience with AI and/or machine learning approaches Interest in reproductive health and/or development of clinical tools and algorithms
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algorithmic foundations of quantum adversarial machine learning, an emerging field at the intersection of quantum computing and machine learning. It investigates how the unique capabilities of quantum computing
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conditions. Our work combines traditional statistical methods with advanced artificial intelligence algorithms to identify patterns in disease. We also use qualitative methods to understand lived experiences
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operation of the umFm module unit used in vertical farm which includes handling of soil compost, irrigating of the crops and taking note of the sensors incorporation in the vertical farm inhouse. Job
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key role in developing and producing advanced optoelectronic devices for applications such as quantum technologies, integrated optical sensors, and laser optics. In this EPSRC-funded project, you will
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or more of: the use of micro/nanofabrication and materials characterization tools; computational multi-physics/electromagnetics modelling and/or the application of machine learning algorithms; experimental
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part of the ‘REMIX -TUNE - Redefining The Role Of Mixing In Ocean Overturning And Ventilation’ ERC Consolidator project, which seeks to leverage emerging sensor capabilities of autonomous profiling
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based at the School of Electronics and Computer Science, Southampton. The project is researching, developing and evaluating decentralised algorithms, meta-information data structures and indexing
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. The successful applicant will use state of the art inference algorithms to design, use and share the findings of epidemiological models that integrate across large and diverse datasets including capture-mark