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metrics for reducing the environmental impact of AI and cloud computing Empirically evaluate different parts of the AI lifecycle, including development (training), operation (inference) and use Develop
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for the analysis of the sequence data, to describe the genetic diversity between French regions for different types of variants (SNV, indels, SV, STR, mictochondrial…). He/she will work in collaboration with our
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variables related to the weather conditions, road surface micro- and macro-texture, tire properties, driving speed, and behaviours of road users. This project aims at studying different data sources such as
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, flexible working arrangements, staff engagement forums, campus facilities and services to support staff from different backgrounds. We are proud to hold Juno Champion and Athena Swan silver awards, which
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generally to develop new distributed edge services. The successful candidate is expected to evaluate metrics such as latency, throughput, availability, and resilience in different applications scenarios
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processes for data standardization, data warehousing, quality assurance development and data analysis. A successful candidate will work closely in different aspects of the quality assurance and data
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You will collaborate closely with RCA staff, PhD students, and external partners, contributing to cutting-edge, design-led robotics innovation. Outputs are expected to be published in high-impact
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help Sony Interactive Entertainment Europe LTD to understand the impact of delay and impairments found in many cloud-based gaming environments. The work will also investigate how to measure different
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diverse academic backgrounds to contribute to our projects in areas such as: Network Security, Information Assurance, Model-driven Security, Cloud Computing, Cryptography, Satellite Systems, Vehicular
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. the investigations into the physical consistency between different satellite-derived climate data records (e.g. aerosol and cloud properties), and the impact of inconsistencies in the data on applications. the quality