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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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premises, you will be undertaking planned projects and reactive work on various systems to support the University’s infrastructure and environmental control systems across all our premises, ensuring
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such as the National Security and Investment Act and Export Control legislation. Collaborating with stakeholders, this role will lead on the delivery of expert advice, guidance, training and support to
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related disciplines. Applicants with track records or experience in system modelling, machine learning and control are highly desirable. How to apply Applications should be submitted via the Chemical and
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variable acoustics room enabling reverberation times as well as room volume to be precisely controlled. Our vision for AURORA³ is to bring the A³ (audio, acoustics and AI) community together, produce high
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Ansible playbooks and roles using git for version control, change management and collaboration. Pro-actively and reactively identify, diagnose, and resolve faults and areas of suboptimal performance across
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environmental control systems across all our premises, ensuring that they are maintained in a safe, efficient, and functional order. The post will be required to support our current day pattern of 08.00 – 16.12