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Overview About the Role Applications are invited for a motivated and committed Machine Learning Engineer. The successful candidate will contribute to Queen Mary’s national reputation for research by planning
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About the Role Applications are invited for a motivated and committed Machine Learning Engineer. The successful candidate will contribute to Queen Mary’s national reputation for research by planning
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generative AI and machine learning to detect code smells and security flaws. We are eager to move forward with the interview process for the Machine Learning position at Haultech Ltd. To better understand your
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Machine Learning techniques to this data to extract the essential information contained within these trajectories. This will be achieved through the following steps: Develop tools to efficiently generate a
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Project title: Machine Learning models for subgrid scales in turbulent reacting flows Supervisory Team: Temistocle Grenga, Ed Richardson Project description: Supervised deep convolutional neural
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Applications are invited to a Postdoctoral Research position, working in the implementation of machine learning methods to better reduce spectroscopic data from JWST and Hubble with Dr Hannah
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We invite applications for the position of Postdoctoral Research Associate in Machine Learning/Machine Learning Scientist to join the Deep Medicine programme at the Nuffield Department of Women’s
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Contract type: Open ended Work hours: 35.0 hours per week The role Applications are invited to a Postdoctoral Research position, working in the implementation of machine learning methods to better
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genomics/transcriptomics, computational biology and machine learning. The overarching aim of the project is to develop strategies to treat patients with rare genetic disorders at scale. Duties will include
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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