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180005 - Research Assistant (Centre for the Study of African Economies) University of Oxford – CSAE, Department of Economics Project Title: Shock-Responsive Social Protection and Climate Resilience
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AI-electronic systems, ensuring secure communication and operation. Side-Channel Attack Mitigation: Implement techniques to protect systems against side-channel attacks, safeguarding sensitive
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-disciplinary collaboration, and professional development opportunities. The research team is embedded within Lancaster’s Security and Protection Science initiative (https://www.lancaster.ac.uk/security-and
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The project is part the NIHR-funded Health Protection Research Unit for Emergency preparedness and response (EPR-HPRU), in collaboration with the UK Health Security Agency (UKHSA). This studentship is funded by
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PhD Studentship: Dissecting the Molecular Architecture and Function of LMTK3 as a Therapeutic Target
; University of Sussex | The City of Brighton and Hove, England | United Kingdom | about 2 months agowill require an IELTS score of 6.5 overall or equivalent proficiency - English language requirements Applications are particularly welcomed from candidates with protected characteristics – e.g., from
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cybersecurity of cyber physical systems and protection against disinformation in social media. Thanks to these successes, the university is now one of only nine in the UK recognised as Academic Centre
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mitigation systems, commonly used in different fields such as seismic protection, which will be tailored for deep-water fixed-bottom applications. This PhD will identify and investigate the technical
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, mitigate health inequalities, and strengthen social cohesion. This project is part the NIHR-funded Health Protection Research Unit for Emergency preparedness and response (EPR-HPRU), in collaboration with
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phdPrimary supervisor - Prof Yongping Bao High consumption of cruciferous vegetables can reduce the risk of cancer. This protection has been attributed to isothiocyanates (ITCs) in such vegetables
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, multi-source learning is used to integrate diverse patient populations to build robust models, but having to protect sensitive information. Various modern ML paradigms are proposed to address the diverse