3 risk jobs found

Bristol, Cardiff, London, Manchester Job Summary The AI Security Institute is the world's largest and best-funded team dedicated to understanding advanced AI risks and translating that knowledge into action. We’re in the heart of the UK government with direct lines to No. 10, and we work with frontier developers and governments globally. We’re here because governments are critical for advanced AI going well, and UK AISI is uniquely positioned to mobilise them. With our resources, unique agility and international influence, this is the best place to shape both AI development and government action. Job Description The Talent team is responsible for scaling AISI from the ground up. This is not your normal civil service team – we have built a reputation for getting things done, challenging the status quo and navigating ambiguity. Our talent pool is highly technical, world leading and in-demand - AI Researchers sit in the most competitive talent field in the world, and we...

Project advert The democratization of finance is transforming global asset management. Retail investors, empowered by trading apps and AI-driven platforms, now control a rapidly expanding share of global assets projected to reach 62% by 2030. While this growth fosters financial inclusion, it also creates new and underexplored risks at the intersection of technology, human behaviour, and market structure. This PhD project will investigate systemic financial risks emerging from the convergence of agentic artificial intelligence and retail trading platforms. Using a combination of experimental analysis, threat modelling, and proof-of-concept demonstrations, the research will identify and map vulnerabilities that may impact both individual investors and global financial stability, as well as evaluate their broader socio-economic implications. The successful candidate will join a multidisciplinary supervisory team of experts in AI, cybersecurity, and finance, based in the...

Project advert Electric vehicles (EVs) are revolutionising transport, but their charging infrastructure faces growing cyber security and privacy risks. Many public chargers lack robust protections, leaving users vulnerable to data misuse and cyber attacks. Current AI-based security tools often act as “black boxes,” generating alerts without explanation, undermining users' trust and slowing adoption. This PhD project will develop a Confidential and Explainable AI framework for EV charging networks. You will explore cutting-edge techniques such as privacy-preserving analytics, Trusted Execution Environments, and federated learning, combined with interpretable anomaly detection and adaptive consent mechanisms. The aim is to keep sensitive data secure while providing clear, actionable insights to users and operators. You will gain expertise in cyber security, AI/ML, and human-centred design, working in state-of-the-art facilities and collaborating with industry and transport...