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(including microscopic studies of samples) and subsurface scales, using reflection seismic and well data. The applicant should have some knowledge or experience of deep learning for analysis of geological data
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within the project, participate in relevant summer schools including one focussing on North Sea hydrocarbon seepage, participate in international scientific conferences, and participate in geological field
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have some knowledge or experience of deep learning for analysis of geological data, preferably with the use of reflection seismic and well data. The applicant must hold a valid driver license in Europe
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habitable using integrative approaches from paleobiology, statistical modelling and paleogeography, using new fossil and geological field data from Mistaken Point and Discovery Geopark, Newfoundland, Canada
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outcomes will lead to better understanding of the geological heterogeneity of reservoir, seal and overburden rocks that may impact seal integrity, fluid injectivity, storage performance, plume evolution, and
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of geoscience? Improve deep learning methods for multi-modal image data applied to industrial challenges in the energy sector? Advance the use of seismic tiles for extracting information about geological layers