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Field
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prototype (MIDAS) that integrates AI-based modules with optimisation engines to support low-carbon, cost-optimal datacentre microgrid design. To manage prototyping of the software platform - overseeing build
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seamless hardware/software integration, aligned with Industry 4.0 principles Numerical and process simulation models to identify optimal mesh sizes, structural integrity, thermal management, and efficient
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include the modification of existing optimization procedures to explore the potential energy surface of materials in search of transition states and structural transformations using existing and newly
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been shown to accelerate and improve the training procedure of SNNs by defining new cost functions that are differentiable and easier to optimize. They can also handle quantized weights, e.g., using
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brand reach. Ensure content consistency and performance optimization. Collaborate with the Global Social Media Manager to define KPIs and identify opportunities for growth and experimentation. Manage and
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laboratory layout regularly, plan and organise layout to ensure optimal workflow. Respond to duties assigned by academic leader/laboratory manager and prioritise accordingly. Forward plan to ensure to ensure
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be used to analyse facilitated workshop outcomes and stakeholder learning and communication. · To make recommendations on the optimal sequence of activities in model-based facilitated workshops
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workshops as a means to continuously improve technical and theoretical knowledge. Ability to obtain information from literature and from colleagues and integrate this into developing and optimizing work
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designing and developing experimental equipment suitable for containing the liquids at the temperatures needed, as well as optimizing the quality of the data obtained, both through experiment design and
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research which combined efficient optimization and sequential reliability assessment. The project is funded through an EPSRC call to accelerate research outcomes to achieve a prosperous net-zero and is