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Field
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with a focus on describing nucleon-nucleonshort-range correlations (SRCs). The successful candidate will bridge the gap between precision experimental data and modern theoretical frameworks, transforming
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 18 days ago
); and propagation of physics-traceable soil moisture uncertainty into precipitation estimates. Machine learning approaches are welcome as tools within this framework — for example, learning the space–time
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datasets spanning the mammalian tree at a scale that would be impractical through manual curation alone. The Postdoctoral Researcher will play a leading role in developing the dietary ranking framework and
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contribute to an integrated modern geoscientific framework characterizing the geothermal potential of the system. The initial appointment would be for one year. Previous experience in one or more of the
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the modeling framework appropriate to each scientific question and dataset. Assess data limitations, identifiability, and model assumptions, and identify additional measurements or experiments needed
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extracting transport properties from molecular dynamics trajectories. ● Experience with GPU-accelerated machine learning frameworks (for example CUDA, PyTorch, or GPU-enabled LAMMPS). ● Experience
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learning frameworks such as TensorFlow and PyTorch. Familiarity with digital pathology, biomedical imaging, or spatial omics data analysis. Experience using version control systems (e.g., Git) and scientific
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simulation framework for non-Newtonian properties of biocompatible ionic liquids and deep eutectic solvents. This position will focus on deriving mathematical equations and implementing them in coarse-grained
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/Systems biology domain): * AI & Computational Side: * Experience or familiarity with LLM/Agent frameworks (e.g., LangChain/LangGraph, AutoGen, CrewAI, Hugging face ecosystem, MCP) and fine-tuning
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the distributed hydrologic model ATS (The Advanced Terrestrial Simulator), coupled to a trait-based plant-soil-microbe model (ATS-EcoSIM). The code provides a framework for three-dimensional hydrologic