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mathematics, programming, and machine learning. *Interest or experience in wireless communications, signal processing, or 6G technologies. To apply, please contact the main supervisor; Dr. Zahra Mobini
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, an important concept within physics, chemistry and biology, but one that lacks a full mathematical understanding. This project will tackle questions relating to universality within the KPZ class of models. Some
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candidate will utilise multiscale modelling, mathematical optimisation, machine learning, and additive manufacturing to create digitally-designed, patient-specific smart implants. To deliver on the project
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challenges in engineering Desirable: Experience with mathematical modelling, optimisation techniques, or supply chain analysis Background knowledge in bio-based materials, biorefineries, or circular economy
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, at least a 2.1 honours degree or a master’s (or international equivalent) in a relevant science or engineering related discipline. Strong background/skills on machine learning, mathematics, probabilistic
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) at the master’s level (at least a 2.1 honours) in a relevant science, mathematics, or engineering discipline are especially encouraged to apply. Additional requirements: Demonstrated determination and resilience