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million in losses each year, with landslides during earthquakes leading to over NZ$1 billion in damage for a single event. While landslide susceptibility modelling is an essential tool in risk management
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research team. Good knowledge and experience in heat and mass transfer is essential and proficiency in the use of Computational Fluid Dynamics will be considered an advantage. The student will benefit from
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and deterministic AI outputs is critical. This requires robust design principles and architectural changes to reduce variability and integrate smoothly with industrial control systems. Enhancing
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increasingly important. The aim of the project is to explore the collaborative dynamics of agents within eCPS, with a specific focus on aligning their behaviours towards achieving sustainability goals. Cranfield
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load emulation, surface tribology and lubricants, contact mechanics or dynamical phenomena. This is an opportunity to work within a world-class multidisciplinary team within the Engineering Systems
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of tomorrow and creating novel solutions to major global challenges. Our community is made up of 13 000 students, 400 professors and close to 4 500 other faculty and staff working on our dynamic campus in Espoo
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, curious individual to join an exciting PhD. This opportunity is generously funded by John Crane Ltd, a world-renowned engineering technology leader. Why This PhD? Impact Clean Energy's Future: Develop next
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, usability, and insight into leakage dynamics across diverse constructions. Research Objectives The project is structured around three synergistic work packages: Descriptive Analytics: You will conduct a
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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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Build Test Solutions Ltd (BTS). This is a fantastic opportunity to work towards a PhD whilst working with both academia and industry. We are looking for a self-motivated student, with an inquiring mind