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different environments influence behaviour and wellbeing. Advanced analytics, including AI and machine learning, will be used to interpret behavioural and emotional data, enabling real-time insights
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, computer simulations and machine-learning analyses. The University of Nottingham offers a wide range of employee benefits. More information can be found at: https://www.nottingham.ac.uk/hr/your-benefits/a-z
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Professor level. The ideal candidate will be at the forefront of research that integrates modern machine learning methods with economic theory and econometric analysis. We are particularly interested in
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Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 36-month PhD studentship will contribute to cutting-edge advancements in automated drug discovery through
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. What you should have: A 1st degree in physics or engineering. An interest in optics, some ability in computer programming A desire to learn new skills in complementary disciplines. You will work jointly
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proficiency in Python (e.g., NumPy, Pandas, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with supervised
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years and in the relevant areas of Machine Learning / Artificial Intelligence, Credit Risk Modeling and Operations Optimization Modeling; The candidate must have strong programming skills in Python, and
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Intelligence, Machine Learning, Software Implementation and Testing, and their applications in manufacturing, transport, healthcare and others. About You The position holder will teach core undergraduate and
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filled The overarching aim of this project is to find synergies between methods and ideas of modern machine learning and of statistical mechanics for the study of stochastic dynamics with application
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-volatile memory that is seen as a potential candidate for the replacement of Flash and SDRAM memory. However, it is their ability to emulate the memory and learning properties of biological synapses and