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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
infrastructure resilience, computational geomechanics, and data-driven risk evaluation. The successful candidate will publish in high-impact journals and contribute to proposals and collaborative efforts within
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the development and coupling of numerical methods for solid mechanics modeling Experience in digital rock technology, including advanced imaging and related analysis Experience in the performance of high pressure
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medical datasets (e.g., electronic health records data or medical images) Ability to use high performance computing cluster For consideration, applicants need to submit a cover letter, curriculum vitae with
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datasets (e.g., electronic health records data or medical images) Ability to use high performance computing cluster Proficient programming experience in Python and libraries (e.g., Pytorch, TensorFlow
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through computer simulations and/or experimental validation. The PDA is expected to actively disseminate results through publications in high-impact journals and presentations at leading international
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. This involves the development of mathematical models for signal transmission/reception, derivation of performance limits, algorithmic-level system design and performance evaluation via computer simulations and/or
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semantics and spatial reasoning. AI for Physical Systems – Leveraging machine learning and AI to improve performance, safety, and adaptability of robots, autonomous vehicles, and other intelligent machines
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, including advanced imaging and related analysis Experience in the performance of high pressure and temperature triaxial tests Experience in experimental rock mechanics Postdoctoral Associate Employment
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performance and robustness, and (ii) exemplary passion and motivation to pursue multidisciplinary research at the intersection of computing and healthcare. Methodologies of interest include: Multi-modal
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models for signal transmission and reception, derivation of fundamental performance limits, algorithmic-level system design, and performance evaluation through computer simulations and/or experimental