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Field
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prototype/demonstrator of a low-cost smart sensor. To develop an efficient algorithm to process the vibration signals locally and to develop the firmware to be embedded within the sensor node. To validate
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to support condition-based predictive maintenance for gas turbine engines. Cranfield has developed unique physics-based technologies on gas turbine performance simulations, diagnostics, prognostics and lifing
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itself and changes the way it should appear at high photon energies. The details of this process can be explored both analytically and numerically, the latter using simulations of magnetohydrodynamics (MHD
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developing experimental therapies such as phage therapy. The candidate should have a good degree in a physical science and an interest the development of new diagnostic systems. If you wish to discuss any
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-efficient research that prevents fatigue failures has pushed towards integrated computational materials engineering approaches that improve competitiveness. These approaches rely on physics-based models
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with a first class or upper second-class degree in engineering, physics, applied mathematics or a related field. A solid foundation in fluid dynamics and heat transfer, and experience with computer
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of these complex designs will need advanced measurements from early development to flight testing. Optical sensing can provide high-resolution data to understand the underlying physics, potentially reducing
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biomedical engineering). Flexible start date! What You’ll Need A first-class or upper second-class honours degree (or equivalent) in Engineering, Physics, or Applied Mathematics. Experience in coding and CFD
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, academia, government, and policy. The interview process is composed of two interviews. Following a first introductory interview (20min), a second online (or face to face if preferred) interview will be
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industry, academia, government, and policy. The interview process is composed of two interviews. Following a first introductory interview (20min), a second online (or face to face if preferred) interview