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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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role brings rewarding and empowering contact with academic, research staff and students alike. We value a flexible approach and willingness to learn as well as develop new professional skills. Within
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environment. In this role, you will lead the computational strand of the project, applying molecular simulations, data analysis, and machine learning to uncover how molecular structure, charge, and surface
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also developing skills in data analysis and machine learning. This role offers a unique opportunity to grow as a researcher, contribute to high-impact publications, and shape the future of biomolecular
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expertise in a supportive and innovative environment. In this role, you will lead the computational strand of the project, applying molecular simulations, data analysis, and machine learning to uncover how
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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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Failure Analysis of Composite Sleeves for Surface Permanent Magnet Electrical Machines This exciting opportunity is based within the Power Electronics, Machines and Control (PEMC) and Composites
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unique combined system using an optimised AF scanning procedure that integrates Raman measurements to analyse lymph node biopsies within 10 minutes and machine learning algorithms to deliver quantitative
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and machine learning algorithms to deliver quantitative diagnosis without destroying the samples. The AF-Raman prototype will be integrated and tested in the operating theatre at the Nottingham Breast
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and its stakeholders. You should hold a Master’s or PhD (desirable) in Computer Science, Artificial Intelligence, Machine Learning or a closely related field. We are looking for a candidate who has