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are invited for a fully funded Industrial Doctoral Landscape Award in partnership with Siemens Digital Industry Software, focused on advancing the next generation of industrial Computational Fluid Dynamics (CFD
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we are looking for The candidate should have a 1st or high 2:1 degree in mechanical/aerospace/manufacturing engineering, computer science, physics, mathematics, or related scientific disciplines
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). The WIRe programme offers a bespoke training programme in technical and personal skills, and access to world-leading experimental facilities. The successful candidate will also have the opportunity
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Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How To Apply Please read and complete this document as your Personal statement, and upload
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industrial practice relies heavily on empirical optimisation, leading to inefficiencies in energy use and impurity removal. This PhD project proposes to develop a Coupled Computational Fluid Dynamics-Discrete
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. Diversity and Inclusion at Cranfield We are committed to fostering equity, diversity, and inclusion in our CDT program, and warmly encourage applications from students of all backgrounds, including those from
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undergraduate degree (or international equivalent) in Engineering, Industrial Engineering, Manufacturing Engineering, Systems Engineering, Operations Management, Computer Science, or a related field. A master's
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. This PhD project will address these critical gaps through an ambitious translational research programme combining human studies with cutting-edge laboratory science. The student will design and lead a
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) at the Rutherford Appleton Laboratory (RAL) in Didcot. This is an exceptional opportunity to work at the interface of artificial intelligence, computational imaging, and life sciences, supported by the Ada Lovelace
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engineering excellence needed for the aerospace sector. In this PhD, high-fidelity two-phase Computational Fluid Dynamics (CFD) methods will be used to model complex and fundamental cryogenic hydrogen flows