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This post will advance the application of Machine Learning (ML) in weather forecasting and hydrological prediction. The Research Fellow will develop ML methods for postprocessing numerical ensemble weather
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contribute to the development of next-generation modelling frameworks that combine physics-based hydrodynamic modelling with artificial intelligence (AI) and data-driven methods to better predict contaminant
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to concentrate on innovative metasurface-engineered tubular designs, advanced ceramic manufacturing, and high-temperature performance evaluation. The project involves developing a mini-scale tubular high
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development. This includes (as examples) researcher with qualitative research expertise (including intervention co-design), expertise in epidemiology/biostatistics, including the use of routine health and care
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cutting-edge data from new ground and space-based facilities to address fundamental questions in galaxy evolution? Then this might be the right opportunity for you. The Astronomy Group within the School
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generated quickly and regularly. Help develop machine learning techniques for feral swine abundance in data sparse environments. Collaborate with APHIS Wildlife Services (WS) to integrate data and model
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the topic of the Futures of Work, to develop our understanding of how foresight informs strategy. The Futures of Work topic might include aspects such as: The nature and meaning of work, including
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science into benefits for human health and the economy. About the role Our lab aims to understand how functional organs are built during embryonic development, an important problem in biology with
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the development of novel DNA Damage Response (DDR) therapeutics. Job Description Develop strategies and conduct experiments to diversify the lead molecule into second-generation compounds with a better therapeutic
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fellow to join our studies on the genetic basis of human evolution, with a focus on the evolution of the human brain. Candidates with a strong track record in any biological field are welcome to apply