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Field
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grid data and/or numerical modeling output from weather and climate models. Prior contributions to open-source scientific software projects. Familiarity with DevOps/GitOps practices including CI/CD
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research activities including laboratory experiments, numerical modelling (FEM/CFD), and development of AI models to optimise drilling processes. Translate research into outcomes by building prototypes
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distribution systems. Current research initiatives include developing advanced vibration analysis methodologies for wooden packaging systems, predictive modeling for packaging performance, and optimization
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candidate will : • Adapt the AEROTYPro/GRASP methodology for the typing and quantification of stratospheric sulfate aerosols; • Develop optical models for the characterization of sulfate particles produced
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activity focuses on understanding the scalar sector of the Standard Model by considering both the Higgs boson and Nambu-Goldstone states. The selected candidate will be able to contribute, in particular
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, improving faculty pre- and post-award service, strengthening compliance support, generating better research intelligence, and creating a scalable model for responsible AI use in research administration
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About the Opportunity Summary: Research involves developing and implementing material models to predict microstructure, phase change and residual stress in processes in high energy processes in
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by Jun Ye and Eric Cornell, is responsible for the current most stringent limit on eEDM. Our goal is to break the Standard Model of particle physics or else set important new constraints trying. We
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processing. 3, Demonstrated expertise in the modelling, design, and optimization of acoustic transducers and metamaterials, with a solid understanding of acoustic wave physics and numerical simulation methods
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. Possible research topics include: Scientific machine learning Numerical partial differential equations (PDEs) Computational fluid dynamics Neural operators High-performance computing Data-driven