254 distributed-computing-"St"-"Washington-University-in-St"-"St" positions at University of Sheffield
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programme grant on hybrid energy storage systems for grid-independent EV charging stations and there will be significant opportunities for the successful candidate to interact with the interdisciplinary team
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Hybrid Multi-Laser Laser Powder Bed Fusion for Next-Generation Metallic Components School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Dr K Mumtaz Application Deadline: Applications accepted all year round Details About the Project The additive manufacturing...
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Multi-Material Laser Powder Bed Fusion for Next-Generation Additive Manufacturing School of Mechanical, Aerospace and Civil Engineering PhD Research Project Self Funded Dr K Mumtaz Application Deadline: Applications accepted all year round Details About the Project The additive manufacturing...
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Overview Are you experienced in using applied maths to model an acoustic problem and analyse data? Do you enjoy working collaboratively? This role offers an exciting opportunity to apply your modelling and analytical skills in building and testing an acoustic monitoring tool to detect hidden...
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Sustainability and resilience of Socio-Technical Systems School of Electrical and Electronic Engineering PhD Research Project Self Funded Dr G Punzo Application Deadline: Applications accepted all year round Details The increasing complexity of our engineering, social, urban, and ecological...
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Machine tool dynamics-based digital twins for real-time monitoring of cutting tool conditions in smart manufacturing
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, transcriptomics arrays and serological assays will be exploited to investigate biomarkers in cultured cells (primary supervisor). Field work at the Malawi Liverpool Wellcome Trust Clinical Research Programme will
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that operate with minimal computing, sensing, and actuating resources—essential features for implementation in real-world scenarios. To this end, we will leverage sophisticated mathematical tools such as
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Multi-Material Laser Powder Bed Fusion for Next-Generation Additive Manufacturing
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). • Eligibility: First degree and Masters in one of engineering and computing fields • Standard departmental requirements: First Class • Experience in physical modelling and machine learning, interest in medical