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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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willingness to learn new skills and undertake further training and development aligned to the role, which may include working with laboratory animals Experience in working in a scientific laboratory, including
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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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background in Computing Science/Cyber Security/Computer Networks/Software Engineering or combination of both with relevant IOT/AI, IT, programming skills (C++, Python, Java or C#, OS etc.), CISCO Networking
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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
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feedback using machine learning and control engineering methods. The project will be hosted at the Bristol Robotics Laboratory (BRL), the UK’s largest academic centre for robotics research, with access
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particular emphasis on preparing analysis-ready datasets that support downstream statistical and machine learning workflows. What you would be doing You will contribute to data access workflows, database and
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support the University’s Health and Safety Policy. To be confident and able to use and instruct on Domestic and Dubied knit machines, and linkers, to produce garments and knit swatches to a high standard
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Adversarial machine learning - Identification and prevention of cyber-physical attacks on infrastructure (S3.5-MAC-Champneys)
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commitment to widening opportunity through the power of education and contributing our talents to creating a fairer world, and a more prosperous region. We are putting inspirational learning and impactful