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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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projects ranging from score-based generative models, energy-based models, Bayesian analysis of graph and network structured data, highly multivariate stochastic processes; with data applications ranging from
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medication use Applying frameworks such as the Andersen Behavioral Model (ABM) and 4Ms of Geriatrics Conducting advanced data analysis and predictive modeling Engaging patients, caregivers, and health system
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could include topics related to ice and volatiles, planetary thermophysics, surface and subsurface characterization, radar remote sensing, and/or the integration of spacecraft data with modeling. You can
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using R for statistical analysis and in statistical modeling. Sound working knowledge of unix shell, high performance compute clusters and git. Willingness to learn and use a scripting language (e.g
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techniques including deep neural networks and large language models (such as GPTs), with state-of-the-art functional genomics approaches, including crop genomics, genome editing, and single cell multiomics
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modeling. Contribute to and drive forward the project’s work plan and study goals. Ideal Candidates: The ideal candidate will hold a Ph.D. in Biology, Biochemistry, Epidemiology, Genetics, Genomics
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forward-thinking model for research—integrating Purdue’s academic excellence with the dynamic opportunities of Indiana’s largest city. This strategic approach fosters transformative discoveries, while