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algorithms and deep learning models. Have proficiency in Python in a Linux environment and development experience using Tensorflow or PyTorch. Have strong linear algebra and computer vision knowledge. Have
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comparing our experimental observations to predictions made using the Standard Model of Particle Physics. I am a member of the LHCb collaboration, one of the four large experiments at the Large Hadron
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Council) PhD scholarships are funded via the ARC discovery project “Modelling, Design and Development of a Novel Wave-Energy Converter”. The purpose of these scholarships is to support outstanding students
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on animal models of glioblastoma to evaluate the effectiveness of the selected DDS in tumour growth inhibition, survival rate, biocompatibility and brain targeting efficiency. Aims • Develop a novel and
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to apply: Seismic wave propagation theory; seismic data acquisition and processing; signal processing, seismic imaging, geophysical inversion, scientific programming, reservoir modelling. Previous research
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My research interests focus on the stars - primarily their structure, evolution and nucleosynthesis. This can involve modelling of mixing in stars, or effects of changing nuclear burning rates
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the development of numerical methods for astorphysical fluid dynamics and radiation transport. Projects may employ a range of approaches from analytic modelling and numerical calculations on desktop
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I supervise a wide range of projects stellar astronomy. They include modelling stars in 1D or 3D, deciphering the origin of the elements (stellar nucleosynthesis), and observing using optical
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that are found readily available in the food supply. In animal models, emulsifiers cause inflammation in the gut, similar to that seen in Crohn’s disease. This project aims at investigating if removing emulsifiers
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I am an experimental particle physicist that works on the search for phenomena that are beyond our current theoretical understanding in terms of the Standard Model of Particle Physics. The research