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guiding impact, capability science and world-class talent within a critical research group Use your collaboration & engagement expertise to advance Mine Geoenvironment’s world class numerical modelling
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. Robert Mann (University of Waterloo), as well as a team of HDR students. The research will explore quantum aspects of physical black holes, collapse models, and the properties of ultra-compact objects
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numerical analysis or modelling of (palaeo)environmental data using R/python/Matlab or similar platforms. Experience with sediment analysis, which may include palaeoecological techniques, sedimentology
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completion of a PhD in geomechanics, energy engineering, geophysics, and/or geodynamics. An established record of scientific achievements in geomechanics and geomechanical numerical modelling, including
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). Proficiency in numerical modelling, data analysis and instrument control in languages such as Matlab, Python, C/C++, etc. Familiarity with sensor technologies and applications, machine learning, and electronics
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of Mechanical and Mining Engineering, where innovation meets impact. As a key member of this dynamic team, you will develop cutting-edge computational models of two-phase flow in fractured media — ranging from
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display excellent data analysis skills, have an eye for detail, and a desire to lead a change through process innovation. Your responsibilities will include budgeting, planning, modelling, forecasting
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experience (or equivalent experience in engineering practice) and expertise at an appropriate level in geotechnical engineering Expertise in either geotechnical centrifuge modelling, field testing or numerical
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(desired) Skills in numerical modelling or programming (e.g., Python, PHREEQC, MODFLOW) (desired) Experience in both qualitative and quantitative hydrogeological methods (desired) This position is open to
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at St Lucia in the Business School. Key responsibilities will include: Engineer, prototype, validate and deploy statistical, machine learning models and analytic solutions to solve challenging problems