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safety and computational social choice and develops formal frameworks and algorithms for eliciting, aggregating, and analysing stakeholder preferences over risk and safety in AI systems. The Research
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or signal analysis, data engineering, and healthcare data governance. Adept at developing/validating AI algorithms, and adhering to regulatory and privacy standards. Desirable: PhD in Computer Science, AI
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Overview We are seeking an experienced researcher to lead the development of decentralised swarm mapping and localisation algorithms for underground pipe operations as part of an international
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to evaluate and advance machine learning algorithms for one of the following application areas: “Characterising forests variations in relation to distance from pre-Columbian earthworks in the Amazon forest
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aims to develop algorithms for discovering patterns that are robust to data changes. They are expected to co-develop the problem definitions, design reslience measures, co-developing and implementing
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opportunity for an experienced researcher to lead the development of decentralised swarm control algorithms for underground pipe operations. You will join an international research programme funded by
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at King’s on quantum algorithms and numerical methods for many-body dynamics beyond the reach of standard classical simulation. About the role We have a high preference for a candidates who is willing
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algorithms, validated in real-time simulations and experimentally in collaboration with industry. The project: This project looks at the development of electromechanical friction wheel braking (EMB) systems
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concurrent algorithms can themselves be vulnerable. In particular, well-understood safety conditions such as linearisability do not guarantee security, and current approaches to addressing this issue lead to
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algorithms. Vision Language Model (VLM) experience is desirable. Qualifications A high-grade undergraduate degree (first class or upper second) in computer science or MSc in related field. Skills Knowledge