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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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measurement requirements, and with the modelling PDRA to support model parameterisation and interpretation of simulation results. Maintain accurate experimental records, contribute to data curation and support
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research delivery, stakeholder engagement, data collection and analysis, and project coordination. The postholder will work closely with academic colleagues, community partners and national stakeholders
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encourage applications from members of groups who are under-represented in our work force including people with disabilities, women and black, Asian and minority ethnic communities. For more information on
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The job information is shown below. Please click on the links to see full details. We’re building a modern, insight led digital experience for our students, applicants and staff and we’re looking
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compliance with programme agreements. Managing reconciliation processes and financial data for TNE and local partners. Liaising with funding bodies and educational partners to ensure accuracy and compliance
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technologies enable our students, staff, researchers, visitors, and partners to confidently and creatively use digital services, technology and data for the benefit of their learning, teaching, research or work
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have collected rich data for understanding the preferences of citizens regarding which policies their governments ought to enact, as well as for investigating where these preferences do and do not exist
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computational ecosystem, including shared codebases, data pipelines, computing resources, and public-facing research outputs (e.g. websites and repositories). They will collaborate across work packages and with
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efficiently. A strong understanding of data protection and the ability to handle confidential information with discretion are essential. We are looking for someone with outstanding communication and customer