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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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are translating our research discoveries into practice, policy and education. Our goal is to: better understand who is at risk of cardiovascular and cardiometabolic disease, identify the molecular pathways
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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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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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Inference Tool (GAMBIT) Community to study theoretical frameworks that extend the standard models of particle physics and cosmology, with the aim of uncovering the nature of dark matter, dark forces, and dark
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of mesons and baryons and their role as indirect probes for physics beyond the standard model. I also follow searches for new physics at the large hadron collider (LHC) and use them to constrain new particles
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models that can forecast the likely outcomes of current practices. The project aims to develop cutting-edge machine learning and statistical risk prediction techniques to predict each short-term, long-term