Submarine channels are the conduits for large volumes of sediment shed from the continental shelf and down the slope to deep-water basins. Channels have a history dominated by sediment bypass and erosion. However, their marginal environments are commonly sites of deposition. Consequently, the sediments deposited in these environments, typified by thin-bedded turbidites, offer a more complete record of the evolution of submarine channel systems than channel axes. These depositional environments, including channel margins, levees and terrace deposits, may interact with topography adjacent to the channels. This project seeks to establish recognition criteria for the identification of thin-bedded depositional environments in a range of submarine slope settings, across systems of different ages and tectonic settings. The study will include fieldwork and core logging in the Karoo Basin (South Africa) and the Peninsular Ranges forearc basin of Baja California (Mexico). In addition, data sets from the Ainsa turbidite system (Spain), plus IODP core data, and sediment cores modern systems will be examined. Techniques will include field mapping, sedimentological logging, construction of photogrammetric models, and compiling digital databases. The margins of submarine channels are also important in terms of stratigraphic trapping of fluids within the channel-fill. To better understand stratigraphic trap potential, 3D petrophysical models will be constructed to understand the likelihood of fluid leakage or seal in these depositional environments, based on careful observations made in the field. Furthermore, the datasets will permit machine learning techniques to be developed in order to help discriminate different sedimentary environments using calibrated core and well logs. The resulting datasets can be applied to subsurface analogues in order to help refine interpretations on depositional environments. This studentship is focused on a topic of international importance and will form part of the Slope5 project, which is an industry-funded research programme. We expect you to submit manuscripts to international scientific journals during the course of the studentship, and to present the results of your research at relevant UK and International conferences. The project will provide excellent training in physical modelling, fieldwork, process sedimentology, data analysis, artificial intelligence in the geosciences, and the development of digital geological models. You will join one of the largest groups in the world working on earth surface processes and sedimentary basins, having access to excellent facilities and the support of supervisors with leading expertise in process sedimentology and the physical modelling of deep-marine sedimentary processes and systems.