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Location: South Kensington About the role: The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple
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at the Hitachi Cambridge Laboratory as well as Dr Ljiljana Fruk's team in the BioNano Group at Chemical Engineering and Biotechnology. Improved enzymes will be combined with nanoparticle catalysts and novel
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. The developed technology will be rooted in causal reasoning, and we envision leveraging causal generative AI methods to develop a rigorous and comprehensive AI testbed. Clinical applications include, but are not
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are looking for: A PhD (or have submitted your thesis before taking up the role) in Materials, Physics, Chemistry or a closely allied discipline Expertise in 4D-STEM data acquisition Expertise in cryogenic
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discounts, travel schemes and many more. To find out more about what we can offer you, follow the link to our benefits website Further information is available in the role profile. To apply for this vacancy
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Professor Akane Kawamura Akane.Kawamura@newcastle.ac.uk For more information on the School of Natural and Environmental Sciences, please click here . To apply, please complete the online application and
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biology, and biochemistry. Plan, conduct, and contribute to experimental work. Identify and develop relevant methods for data collection, analysis, and interpretation. Develop expertise across scientific
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. For more information, please see our website https://www.hw.ac.uk/uk/services/equality-diversity.htm and also our award-winning work in Disability Inclusive Science Careers https://disc.hw.ac.uk/ We
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such approaches would be cost effective. To achieve this, you will be supported to undertake analyses using large data registries such as the Clinical Practice Research Datalink. This is an exceptional opportunity
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made. The project will involve using routinely collected healthcare data and/or large healthcare datasets such as the Clinical Practice Research Datalink. This is an excellent opportunity for someone