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processes that use data-driven machine learning. Given the span of the IN-CYPHER programme, we are seeking multiple motivated research fellows. Unique in its scope, we are developing technologies that span
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processes that use data-driven machine learning. Given the span of the IN-CYPHER programme, we are seeking multiple motivated research fellows. Unique in its scope, we are developing technologies that span
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leading independent higher education provider, offering flexible and inclusive learning across multiple London campuses. We are student-focused, digitally forward, and committed to academic excellence
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leading independent higher education provider, offering flexible and inclusive learning across multiple London campuses. We are student-focused, digitally forward, and committed to academic excellence
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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
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demonstrated ability to work within a geographically distributed networks of collaboration Proven experience in developing and implementing machine learning models and algorithms, ideally in the healthcare
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-sensitive data augmentation and mining Manage multiple stakeholders, meet deadlines, and integrate project outputs into DeltaXignia’s workflows with training Balance technical development and commercial goals
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modes (e.g., HCCI) for net-zero fuels like hydrogen and ammonia. A key innovative pillar is the development of an AI-driven control strategy. Machine learning algorithms, including reinforcement learning
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The KTP project will enable DeltaXignia to augment their Compare and Merge software capability by leveraging Artificial Intelligence (AI). Their current offer is built using mathematical algorithms
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. Expected outcomes include: development of novel algorithms that significantly improve predictive accuracy for equipment failure; creation of scalable monitoring systems that reduce operational costs