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via traditional analytical methods extremely challenging. This project will apply pattern recognition and machine learning techniques to a large database of experimental data to reveal early-stage
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global castings industry. The AMRC Castings Group is a leader in advancing casting technologies and techniques. Our team provides advanced casting expertise, including computer process modelling, design
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will enable the advanced monitoring and computing techniques of power systems, as well as to create a resilient control and operation for both energy network and distributed energy sources. This PhD
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reputation for novel, research-led teaching. Main duties and responsibilities Design an experimental regime and testing methods for battery safety testing of assessing the safety of Li-ion containing theatre
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Self Funded Dr Kristian Groom Application Deadline: Applications accepted all year round Details Research into next-generation additive manufacturing processes based on a new method for selective laser
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. This paves the way for the application of MPC to large-scale systems, since the computational bottleneck is removed. The basic challenge is how to coordinate the distributed decision making of agents so that
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using electric, hydrogen and hybrid power sources have seen rapid developments. This leads to many interesting control challenges. This project will focus on the use of the latest development of numerical
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digital recruitment methods. Build and maintain relationships with key stakeholders Plan and deliver short-term projects in collaboration with colleagues across MARC Assist with the recruitment, training
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through this project. In particular, you will gain training in computational methods. You will also gain experience in pharmaceutical characterisation and manufacturing techniques, particle size and shape
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urgency. This involves drawing upon depth of knowledge, skills, experience and expertise to deal with the job in hand. Make decisions on the methods to be used and the sequence of actions. Undertake