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advance knowledge and improve the human condition. Explore how we are tackling critical challenges at the forefront of biology and medicine, and shaping a healthier, more sustainable future for all. Learn
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the EPSRC progarmme grant on Quantum advnatage in Quantiative Quantum Simulation (QQQS), will involve adapting and using our existing ultracold erbium and potassium machine for studies of e.g. turbulence
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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on type, size, location of data centers in the US, their electricity and water demand, carbon emissions; exposure to air pollution. ● Develop and/or apply methods for causal inference and machine learning
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for a short-term 2.5-month postdoctoral position (full-time) focused on developing and validating machine learning models that predict soil health and crop performance. The position will exploit datasets
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opportunity to collaborate and learn from experts researching, developing, and testing emerging technologies in marine energy and/or ocean-based industries. You will conduct research at both your academic
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 2 months ago
permeability of fluid flow through hydrate-bearing sediments, • High resolution visualizations of hydrate distributions and fluid migration in porous media under in situ conditions, and • Machine learning
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 1 month ago
The ideal candidate would have some, but not necessarily all, knowledge of and skills in: Familiarity with artificial intelligence, machine learning, physics-informed neural networks, or reduced-order
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National Energy Technology Laboratory (NETL) | Morgantown, West Virginia | United States | about 3 hours ago
migration in porous media under in situ conditions, and • Machine learning application to gas hydrate system to develop efficient key parameter estimation tools and large-scale 3D geologic model for gas
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the production of the CBC catalog. The successful candidate is expected to have strong analytical skills and experience with signal processing, Bayesian statistics and machine learning. Exemplary