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our software development team, developing novel scientific algorithms and applications in the areas of spectroscopic analysis and mining of the science data catalogues extracted from the pipelines
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The role will develop new AI methods for identifying the instantaneous state of a fluid flow from partial sensor information. The research will couple techniques from optimization and control theory
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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour
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One Research Associate position exists in the data-driven mechanics Laboratory at the Department of Engineering. The role is to set up a machine learning framework to predict the plastic behaviour
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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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Natural Language Processing (NLP) in the areas of culturally aware NLP or multilingual conversational NLP, and integration of such methods to support language technology in multiple languages
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techniques, data analysis with desirable knowledge of material characterisation, rheology and imaging. Scientific interest, dedication to research and career goal to work in physical science research
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, and Internet-of-Things / Industry 4.0 technologies. Knowledge of computer science principles and modern AI approaches in computer vision and/or time series analysis is a plus. The position requires
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About the Role Join a multi-disciplinary team that explores human intestinal development and disease using cutting edge single cell and spatial biology technologies, organoid models and
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of the structure and use of routinely collected cancer data. In this role, the postholder will act as a liaison between the National Disease Registration Service and the Departments of Public Health