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overcomes the geographic limitations of conventional systems, enabling global scalability and accessibility. Using advanced computational fluid dynamics (CFD) approaches, the project is aimed at advancing
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strategies for robust statistical models. The project’s scope will be tailored to the candidate’s expertise, offering opportunities for innovation and impact. The successful applicant will join a dynamic
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. Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and all become valued members of the Cranfield Doctoral Network
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FPGA/ASIC architectures that dynamically reconfigure based on AI workloads, optimizing performance, energy efficiency, and functionality. 3- Intelligent Interface Design: Create smart interfaces
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/or dynamic analysis of mechanical/robotic systems •Ability to use finite element modelling and to simulate complex mechatronics •Ability to implement control and kinematics with hardware-in-the-loop
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In this position, you will work on microscopy-integrable measurement technologies used to study three-dimensional cell culture models of breast cancer tissues. This PhD candidate position is
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aims to develop a novel theoretical framework for nonlinear and robust control of dynamical systems from a phase perspective. You will have the opportunity to freely explore multiple research directions
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moments. All these factors are highly dynamic in the way they interact to impact racing tactics and trends. The specific objectives include: Historical analysis of racing from the past 3-5 years across
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. Funding This is a self-funded PhD. Find out more about fees. Cranfield Doctoral Network Research students at Cranfield benefit from being part of a dynamic, focused and professional study environment and
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Supervisory Team: Dr. Isha Gupta PhD Supervisor: Isha Gupta Project description: We invite applications for a Ph.D. position focusing on high-performance aerospace materials. As the aerospace sector