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in the area of dynamic system modelling with knowledge of signal processing and machine learning as all three areas are essential to achieve the aims. You should have a proven track record in at least
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combination of geophysical, geological, and petrophysical data with advanced data processing techniques, including multi-component elastic full-waveform inversion, AVO inversion and machine learning, will be
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fields both locally (field by field) and regionally (groups of fields). Data driven analyses will be complemented by physical reservoir modelling, with machine learning approaches to extract correlations
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theory, and topology, with potential interdisciplinary applications. A PhD in Mathematics or a closely related field, as well as an active Christian faith, are required. What You Will Do: Duties include
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previous experience in application of machine learning techniques within energy systems strong analytical skills and ability to collect, analyze and study the impact of low carbon technologies good knowledge