14 machine-learning "https:" "https:" "https:" "https:" "https:" positions at University of Nottingham
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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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optimisation. State-of-the-art digital models and AI tools that incorporate machine learning could enable predictions of the dry fibre forming that are subsequently used as input into the RTM process model
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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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related topic: Strong understanding of power electronics principles Excellent knowledge on data-driven machine learning algorithm and experience in using these algorithm for electrical engineering problems
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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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. 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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-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
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, that consumers still enjoy. By developing novel, cutting-edge technological approaches including computer vision, machine learning and robotics, blended with consumer science, you will be at the forefront
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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