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combining physical models, sensor data, computational methods, and damage and fracture mechanics concepts to create a virtual replica of the composite tank, enabling predictive maintenance, lifetime
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(computer vision technologies). The interdisciplinary nature of this PhD will require the integration of environmental science, engineering, and community science methodologies. Supervisors: Primary
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for 4 years. The PhD project would suit a candidate with an undergraduate degree (2:1 minimum) in computer science, bioinformatics, physics, or chemistry. References: [1] Ludwig C. MetaboLabPy — An Open
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honours MEng/MSci or higher degree (or international equivalent) in: Engineering, Applied Mathematics, Physics, or a closely related field We are also looking for a strong background in aerodynamics/CFD
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multi-disciplinary team Strong communication skills, both written and verbal Qualifications PhD Awarded (for the position as Research Associate) in Mathematics or Statistics or Computer
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Institute, with close ties to the Department of Computer Science and Technology. Preferred skills/knowledge We are seeking a passionate and collaborative PhD student with a strong background in machine
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quantitative connections between the continuum parameters and the underlying microscopic mechanics. Numerical study. Implement the models in computational codes to design and optimize morphing strategies. During
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nature of this programme, we welcome applications if your background is in any biological, chemical or physical science or mathematics and are interested in using your skills in addressing biological
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opportunities. Be mentored by internationally recognised research leaders Our cohort-based, 4-year scheme offers a distinctive PhD training experience. During this structured PhD programme, you will complete
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This fully-funded PhD studentship, sponsored by the EPSRC Doctoral Landscape Awards (DLA), Cranfield University and Spirent Communications, offers a bursary of £24,000 per annum, covering full