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machine learning with spectral data to enable rapid, non-destructive detection of food adulteration and fraud. Machine learning combined with spectral data can play a vital role in combating food fraud by
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into the sample of interest. Recently we have been using AI and machine learning to predict the distortion present and significantly speed up this correction process. This PhD project will take the latest in AI
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to learn. Good organisational and presentation skills. The ability to work well in an interdisciplinary environment. Further information: This position is offered full time, fixed term for 18 months
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IT and AV services that underpin technology-enhanced teaching, clinical simulation and hybrid learning environments. This is a pivotal role ensuring the reliable operation of technology-enabled
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cutting-edge courses, modern pedagogy and practical knowledge, we enable our students and staff to experience the joy of learning, teaching, research and innovation, and apply their knowledge
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knowledge across disciplines and rapidly acquire understanding of other disciplines. Statistical skills including regression models, distributed lag non-linear models, hierarchical models, machine learning
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further developing new and innovative academic practice and learning opportunities working in collaboration with our partners across England. You will work as part of the course team supporting
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through to create outstanding learning opportunities. They will have excellent communication skills, have empathy, understanding and the ability to inspire and engage young people to excel and achieve
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wide range of libraries/frameworks and cloud infrastructure tools. Familiarity with Machine Learning, Neural Network and AI driven image analysis methods Experience with data management for large data
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, and excellent learning and development opportunities. Informal Queries For an informal conversation about this role, please contact Dr Awinder Kaur, Head of Digital Technologies and Machine Intelligence