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Materials Research Center (SusMat-RC) at UM6P. The successful candidate will work on an exciting project focused on extracting and analyzing experimental and computational data to develop predictive models
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The University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 14 days ago
Number: 308854 Vacancy ID: PDS004701 Position Summary/Description: The Lee Lab in the Department of Biology at UNC Chapel Hill is seeking a postdoctoral researcher to advance our understanding
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
following areas: Large-deformation numerical modeling (e.g., Coupled Eulerian-Lagrangian (CEL), Material Point Method (MPM), or advanced Finite Element Methods). Physical modeling of tunnel excavation and
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Moustafa to carry out cutting-edge research in the broad area of future structures and resilient infrastructure systems with interest in applications of new and emerging technologies. Particular areas
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programming or scripting (e.g., Python, Bash, or similar) for workflow automation and data analysis. Familiarity with common tools for structure-based molecular modeling or virtual Ability to think critically
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Your Job: Operando X-ray investigations of energy materials, with a focus on chemical hydrogen storage Design, development, and optimization of advanced sample environments and reactors for high
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gastruloids, organoids, or related 3D stem cell models Proven skills in advanced imaging and quantitative analysis of dynamic processes Interest in interdisciplinary approaches at the interface of biology and
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Post-Doctoral Associate in Sand Hazards and Opportunities for Resilience, Energy, and Sustainability
background in computational modeling, data analytics, and/or automation in construction or infrastructure management. Demonstrated research excellence through peer-reviewed publications. Experience with
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ambitious researcher looking for your next challenge? Do you have an established Are you an ambitious researcher looking for your next challenge? Do you have an established background in modelling
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, combining computational modeling, high-throughput experimentation, and advanced characterization techniques. The position offers substantial opportunities for scientific growth, international networking, and