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scientific knowledge and develop innovative strategies and technologies that will strengthen the nation’s leadership in creating solutions to help sustain the Earth’s natural resources. Our scientists conduct
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physics-informed and physics-ML hybrid approaches that integrate domain knowledge with data-driven methods to advance hydrological process understanding and prediction. Conduct multimodal, multiscale data
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. Knowledge of Python programming language. Preferred Qualifications: Experience with object-oriented programming languages (especially C++), version control system (Git) and software development practices
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within the last 5 years Experience in polymer synthesis, polymer processing, and characterization methods Preferred Qualifications: Knowledge and experience in controlled/living polymerization, particle
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developing large language models. Experience in DNA and protein AI/ML models and multimodal datasets. Knowledge in different deep learning architectures, tokenization and embedding methods. Experience in
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, physical chemistry, chemical physics, or a closely related field completed within the last 5 years. Preferred Qualifications: Experience or knowledge in some of the following areas: (i) classical and/or ab
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techniques. Preferred Qualifications: Knowledge of HPC matrix, tensor and graph algorithms. Knowledge of GPU CUDA and HIP programming Knowledge on distributed algorithms using MPI and other frameworks such as
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salt breeders) is a plus. Experience in the analysis of heat transfer systems. Working knowledge of computer languages such as C++, FORTRAN, or Python. Experience with computer aided design (CAD
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characterizations, and models that are suitable for nuclear fuel performance codes. Knowledge and experience of x-ray computed tomography, mechanical testing, and finite element modelling is desirable. Major Duties
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Postdoctoral Research Associate - Energy materials synthesis and exploration with neutron scattering
team, you will explore the synthesis mechanisms of solid electrolyte and electrode for energy storage materials via ex-situ/in-situ neutron scattering experiments. The knowledge learned from neutron