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. In this role, you will be part of the research team, working to develop and evaluate privacy-preserved Generative AI algorithms for generating synthetic Personal Identity Information (PII). This aims
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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aims to optimize the operations (serving) of AI by developing algorithms that manage compute, network, and storage resources in a carbon-efficient way while supporting long-term benefits
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foundational understanding of children's agency in digital environments increasingly dominated by AI systems. The UCL team is specifically focusing on the educational technology angle, developing agency
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research in fundamental & applied AI that is directly relevant to policy. to develop and deliver expert-led training on AI to civil servants across government. Fellows will spend 50% of their time on each
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. You will focus on developing microwave techniques and associated electronics to precisely control the curing process, using AI-based algorithms to optimise outcomes. Full support will be provided
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Experience in devising and developing novel machine learning algorithms Hands on experience with ROS and physical robots Excellent mathematics skills, particularly in areas relevant to robotics and AI
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Experience with machine learning algorithms and ideally experience developing novel methods Understanding of basic biological principles and experience interpreting ‘omics data Ability to analyse information
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-disciplinary research environment Desirable criteria 1. Experience in devising and developing novel machine learning algorithms 2. Hands on experience with ROS and physical robots 3. Excellent
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. - Collaborating with interdisciplinary teams to design and implement innovative solutions in MLOps. - Developing and optimizing algorithms for model compression and efficiency improvement. - Staying abreast