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an increasingly complex development environment. Areas to consider that impact the modelling are: Framework Language Process How wide / how deep i.e. what do we model and why? How much provides a good answer i.e
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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of Strathclyde will lead the wind energy training and research elements of the programme. Funded by EPSRC, this 4 year PhD studentship, at the University of Strathclyde is in the area of novel wind turbine concept
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control system that enhances Annual Energy Production (AEP), reduces mechanical stress, and improves fault detection using machine learning (ML) and physics-based modelling. The candidate will gain hands
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will provide experience with new and advanced 3D-printing equipment not available elsewhere. This project is aligned with the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which
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PhD Studentship: Dissecting the Molecular Architecture and Function of LMTK3 as a Therapeutic Target
of interest, skills and previous experience, motivation for Doctoral Research, future goals, and why you are applying to this project. On the application system select Programme of Study – PhD
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Cranfield University's tailored researcher training programme – setting you up for a rewarding career in water science and environmental technology. Per- and polyfluoroalkyl substances (PFAS), also known as
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the “Dialling up Performance for on Demand Manufacturing” Programme Grant, which will place the student within an active and supportive team of 9 other PhD students, 15 postdoctoral researchers, 18 world-leading
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equivalent) in Civil Engineering, Environmental Engineering, Hydrogeology, Geosciences, Environmental Sciences, or related STEM disciplines (e.g., Applied Mathematics, Physics, Computational Sciences
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student with an aerospace, mechanical engineering, or physics background. Experience of experimental and computational modelling of icing physics, instrumentation and imaging techniques would be