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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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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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academia. The programme aims to train GP Fellows in health data science, research methods, and the clinical effectiveness approach, to develop them into future academic GP leaders. The post will be split 50
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track record of research income generation. Evidence of effective mentorship, leadership, and collaborative research activity is also essential. Additional Information Unfortunately this role is not
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research and unite our researchers around our Technology Innovation Challenges and Life Science Challenges. For more information on the Franklin’s Challenges click here . As a Research Associate in Chemical
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status, race, religion or belief, sexual orientation, or trans status or history. More information on our structures and initiatives around EDI, including information on staff diversity networks, can be
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-led change, we would love to hear from you. For more information about the role, please view the full job pack here. To apply, please submit: Your CV Supporting statement (this should be a maximum of
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are non-contractual may be amended at our discretion). For further information or in event of queries, please contact the HR Office: Email: recruitment@dow.cam.ac.uk Tel: 01223 334820 Downing College
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however, we recommend that you assess your eligibility before applying for this position. For more information visit the Government Skilled Worker visa support page. However, applications are welcome from
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over one or more core research thrusts within the lab’s multi-agent security programme. You should possess a PhD/DPhil completed, (or near completion), in theoretical computer science, information theory