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, and computer scientists based between University of Bristol and University of Oxford. What will you be doing? The postholder will have responsibility for leading the technical delivery of the work
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ACCE+ DLA Programme: Quantifying water storage beneath the Greenland Ice Sheet and its influence on ice dynamics and runoff School of Geography and Planning PhD Research Project Competition Funded
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BBSRC Yorkshire Bioscience DLA Programme: Predicting pathogen evolution: using experimental evolution to understand the impact of phage therapy on Clostridioides difficile School of Biosciences PhD
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following the renowned "Work-Integrated University-Industry Collaborative Talent Training Model." We offer cutting-edge programs in high-demand fields: Digital Technologies, Computer Science, Logistics
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We would like to appoint an Application Developer to be responsible for the software development of a Greener Trials Toolkit. The Toolkit will be an online, open-access, digital carbon calculator
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About you- We’re looking for someone who leads with fairness, integrity, and inclusivity, consistently creating an environment where everyone feels valued and heard. You will proactively develop and inspire others, offering clarity behind decisions and encouraging accountability across the team....
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Job titleDeputy Dean (Computing) Job referenceRU04980 Date posted09/12/2025 Application closing date31/01/2026 SalaryCompetitive Salary Contractual hoursBlank BasisBlank Job category/typeAcademic
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About the Role This is an opportunity to join an established, high-profile, team that is working on various aspects of cloud computing and AI law. Members of the team also teach on courses in cloud
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PhD at the Forefront of Computational Solid Mechanics and Machine Learning School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Dr J L Curiel Sosa Application
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cutting-edge computer vision technology. Working closely with the Principal Investigator, Co-PI, and interdisciplinary research team, RE will develop and implement deep learning algorithms to analyze trap