393 machine-learning PhD positions at PhD Programme "Gene Regulation in Evolution" in united-States
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implementation of position location estimation using Machine Learning (ML) techniques has been proposed as a methodology to improve performance beyond that of existing techniques, particularly in non-line-of-sight
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machine-learning techniques in ST studies. Our approach introduces two innovations: developing sparse Bayesian learning algorithms for efficient small dataset analysis and designing a simulator for
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telemetry equipment. They will be responsible for ensuring high quality twins, and will interact with the project team on the development of effective machine-learning models to be deployed within these twin
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learning called Machine Listening. The PhD project brings together world-leading audio experts to develop state-of-the-art techniques as a widely-applicable embedding of acoustic environments. Based in
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analytical skills and substantial experience in machine learning at scale are required. Detailed information on the requirements for the role can be found in the further particulars. The position is for 1 year
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EPSRC CASE Studentship. University of Sheffield and Syngenta Crop Protection Machine learning is increasingly used for decision making and molecular design in the pharmaceutical and crop protection
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EPSRC PhD Studentship in: Big Data, Network Complexity and Machine Learning to Deliver Targeted Pro-active DWDS Maintenance Department of Civil and Structural Engineering PhD Research Project
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Turing University Network) and the CitAI Research Centre (which features academic staff with extensive expertise in machine learning for healthcare). They will also be able to exploit the power of Hyperion
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. This PhD project will take advantage of recent developments in machine learning methods, to enable computer modelling of the mechanical behaviour of titanium alloys to produce a machine learning-based
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sustainability analysis through a machine learning (ML) and explainable artificial intelligence (XAI) outlook. The project marks a significant advancement in improving public safety against both low-probability