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Field
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Psychology, Cognitive Sciences, Modeling and Simulation, Computer Science, Measurement and Statistics, or a related field is required. The candidates must have research experience in one or more areas
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structural development over time at the group, sub-group, and individual level (e.g., using normative modelling and clustering approaches to parse heterogeneity). The candidates will further have the
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interested in computational materials design and discovery. The successful candidate will develop new, openly accessible datasets and machine learning models for modeling redox-active solid-state materials
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vivo neuroscience experiments in rodent models of addiction. Design and conduct cutting-edge experiments, lead independent research projects, and contribute to collaborative, multidisciplinary studies
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Stanford University / SLAC National Accelerator Laboratory | Menlo Park, California | United States | about 23 hours ago
analysis from liquid xenon test platforms studying ionization readout for future single- and dual-phase detectors Simulations and sensitivity projections for 0𝜈ββ with the XLZD experiment Beyond
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multi-model large ensemble datasets under the Regional Aerosol Model Intercomparison Project (RAMIP), the Researcher will help quantify the role of aerosols—relative to greenhouse gases—in shaping
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applying: Curriculum Vitae, duly updated, dated, and signed; Copy of academic degree certificates. a) If the possession of a degree is a requirement for the grant, candidates holding a degree
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and simulation tools, such as spreadsheet-based process cost modeling, input/output modeling, or commercially available life cycle analysis tools such as SimaPro and openLCA. Excellent written and oral
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either or both agent-based modeling and social network analysis/network science. The ideal candidate should be able to program in C or C and have experience working with tera-bytes of data. Preference
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and localization of a potential fault using the Matched Field Processing (MFP) method, based on the reconstruction of a response model of the inspected structure from the modal parameters predicted by