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Field
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rules which enable effective learning in large and deep networks and is consistent with biological data on learning in the cortex. In particular, the research will focus on evaluating and extending a
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high fidelity models of ice crystal icing accretion and shedding, verifying tools using the wealth of unique experimental validation data generated by researchers at the Oxford Thermofluids Institute
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large and complex datasets (e.g. geochemical, spectroscopic) for understanding processes involved in the origin and evolution of the Solar System, as evidenced by relevant published work. A successful
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large and complex geochemical datasets for understanding geochemical processes as evidenced by relevant published work. A successful outcome from this work will be a better understanding of the history
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collaborative research group of Professor André Cobb, working at the forefront of foldamer research and cutting-edge synthetic methodologies (for information about the group, please visit http
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knowledge and tools for non-equilibrium flows for hypersonic vehicles. The research will provide unique and high-quality experimental data for expanding high temperature flows. Alongside this, the proposal
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to the ongoing research in Prof. Marcotti’s laboratory by designing, developing and performing experiments, data analysis and disseminating the findings by writing articles and by presenting findings
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/scripting (e.g., in Python, and/or R, and/or Matlab, and/or Bash script & NCO & CDO, etc.) and have demonstrable expertise in the analysis of big data, while the experience with interpretation of climate
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& NCO & CDO, etc.), and have demonstrable expertise in the analysis of big data, and the interpretation of climate/weather observations/reanalyses and model simulations. Additionally, experience with
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-actuated large-scale manipulators (e.g., container cranes). For further information on Dr Antoine Cully’s research and projects, see www.imperial.ac.uk/adaptive-intelligent-robotics This project will be