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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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and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing . This is a full time and a fixed-term contract (36 months ) based
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, University of London in August 2024. As a PhD candidate, you'll become an integral part of the School of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading
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of Science and Technology (proud member of the Alan Turing University Network) and be supervised by leading experts in machine learning for healthcare. You will also be affiliated to the School of Health
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awarded the prestigious Marie Skłodowska-Curie Actions Doctoral Network grant, the AUREUS network is dedicated to addressing the critical global challenge of multidrug-resistant Staphylococcus aureus
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—and career-defining. With a generous scholarship that speaks of trust, vision, and opportunity, this is more than funding—it’s your launching pad to impact the world.
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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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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