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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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. There are opportunities to broaden out into other areas such as new algorithm development, and advanced computational methodologies for integrated analyses. You will have a key role in planning, designing and executing a
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uses, improving the AI and MRI algorithms, and linking them with information from biological studies on tumour tissue. This project harnesses AI to improve diagnosis and clinical decision-making leading
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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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Desirable criteria Experience of advanced statistical and/or machine learning methods, such as longitudinal analysis methods, latent variables models, clustering algorithms, missing data and clinical trial
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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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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