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analyse large, multidimensional 4D STEM datasets. Develop or adapt software tools (e.g. Python, MATLAB) for image reconstruction, phase mapping, and quantitative analysis of ferroelectric domain wall
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Appropriate computational skills and knowledge of programming languages (Python, C++, etc.) Experience with Machine and Deep Learning models and software (Keras, Scikit-Learn, Convolutional Neural Networks, etc
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Europe. Recently awarded the prestigious Marie Skłodowska-Curie Actions Doctoral Network grant, the AUREUS network is dedicated to addressing the critical global challenge of multidrug-resistant
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contribution will have a lasting impact. As a member of our vibrant community of 22,000 students and 8,000 staff, you will collaborate with passionate minds across nine London campuses and a global network. This
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Hypersonics Doctoral Network. This network is supported by the Ministry of Defence and EPSRC for building the necessary expertise to develop next-generation hypersonic vehicles. Objectives: You will investigate
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that have been developed in-house based on the OSIRIS Particle-In-Cell simulation software. The code needs to be verified and further developed with user cases against experimentally gathered data sets
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also be opportunities in the wider community of researchers at UCL to develop new networks. This is a fixed-term role for 6 months in the first instance, with the possibility of extension (3 years in
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of Roehampton) and Mr Bernard Ogden (Research Software Engineer, The National Archives). The student will be expected to spend time at both the University of Roehampton and The National Archives. As part of
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staff, you’ll collaborate with passionate minds across nine London campuses and a global network.
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engineering and can demonstrate through other projects or experiences knowledge across the disciplines of electronics, software development and/or RF communication. An interest in rocketry and/or prior