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Posting Title Graduate PhD Student (Year-Round) Machine Learning Applications for Cyber-Physical Power System Operations Intern . Location CO - Golden . Position Type Intern (Fixed Term) . Hours Per
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to be part of a unique and diverse community that works on high-impact research, educational, business, and societal problems. Position Summary The Machine Learning Researcher - Epidemiology will report
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recently completed a pilot study investigating the use of atmospheric pressure ionisation mass spectrometry coupled with machine learning for differentiating between brain tumours and normal tissue
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Simulation – Data Analytics and Machine Learning (IAS-8) at Forschungszentrum Jülich, which is dedicated to pushing the boundaries of data science theory and application. Our research spans from use-inspired
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descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange isotherm parameters directly from molecular properties. These predictions will be integrated
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the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
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The National Institute of Education invites suitable applications for the position of Research Fellow on a 9-month contract at the Office of Graduate Studies and Professional Learning . Project
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Supervisor: Professor Fernanda Duarte Start date: 1st October 2026 Applications are invited for a fully-funded DPhil studentship in Machine Learning Interatomic Potentials for Metal-Ligand
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Do students receive financial aid? All doctoral positions are fully funded, including social benefits. Students also receive funding to attend conferences and other events related to their research, and have access to outstanding facilities. Do I need to know English? Yes, English is the...
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heavily relies on empirical determination of key model parameters. By combining protein structure descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange