50 molecular-modeling-or-molecular-dynamic-simulation Postdoctoral positions at The University of Arizona
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atmosphere models to simulate observations of ensembles of transiting exoplanets and their host stars to interpret observations with the Hubble and James Webb Space Telescopes, and the NASA Pandora SmallSat
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will be compared to natural prototypes (e.g. in Asia or western North America) and analog models, with emphasis on the implications for structural models needed for energy geoscience. Key skills include
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career scientist with background in organic geochemistry, statistics, and Bayesian modeling to pursue analyses of paleoclimate biomarker data. The ideal candidate should be proficient with both laboratory
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Address Tucson, AZ USA Position Highlights The Lunar & Planetary Laboratory at the University of Arizona has an opening for a Postdoctoral Research Associate I in the field of modeling of planetary
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) spectrometers, and they have been subjects of numerous dryland empirical, remote sensing, and modeling studies. The postdoc will be joining a collaborative team but will also have plenty of freedom to develop
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on Scattering Amplitudes to join the group of Callum Jones, and one with focus on particle physics Beyond the Standard Model to join the group of Shufang Su. Start dates August 24, 2026 or a mutually agreed upon
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) 4+ years’ experience in Matlab™/C++/Python 2+ years’ experience with acoustic modeling software (k-Wave, FOCUS, Field II) 2_ years’ formulating and characterizing nanoparticles or contrast agents
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Address Tucson, AZ USA Position Highlights The Lunar & Planetary Laboratory at the University of Arizona has an opening for a Postdoctoral Research Associate I in the field of modeling of planetary
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Associates with expertise and/or interest in high temperature structural materials, additive manufacturing, non-destructive testing, multi-scale modeling and materials characterization. The ideal candidates
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sequence programming (e.g., IDEA/ICE) and contemporary image reconstruction techniques (e.g., compressed sensing, parallel imaging, model-based or deep learning reconstructions). Knowledge of radial data