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Are you interested in developing screening methods to enable subsurface H2 storage? If you enjoy working at the interface between geoscience and engineering then this project may be right for you
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with 32 active researchers at the assistant, associate or full professor level and currently with 16 PhD students. Faculty cover a wide range of research topics and methods and belong to the top 5
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meter with a non-insulating pipe wall. The research will use existing MHD direct numerical simulations to investigate the flow physics. You will also construct a prototype to test the performance using
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of turbulent pipe flows. In this project you explore novel fundamental approaches of an EM flow meter with a non-insulating pipe wall. The research will use existing MHD direct numerical simulations
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. We will achieve this together by creating the first mathematical framework for explainable AI and developing new explanation methods. This will involve using tools from mathematical machine learning
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numerical methods, as well as familiarity with concepts in complex systems, physical memories or machine learning. We strongly believe in the benefits of an inclusive and diverse research environment, and
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sensors in composites. Strong mathematical background and experience with numerical methods for structural analysis. Proficiency in programming (e.g., MATLAB, Python). You have obtained your PhD degree in
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having and affinity to supporting numerical methods. In particular, we look for a candidate with A PhD in an appropriate discipline, including Aerospace, Mechanical, Civil or Electrical , Materials Science
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composite propellers. Competence in the measurement and analysis of guided waves. Experience with embedded piezoelectric sensors in composites. Strong mathematical background and experience with numerical
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composite materials and structures with an interest in advanced experimental approaches for thermomechanical manufacturing processes while having and affinity to supporting numerical methods. In particular