16 phd-in-mathematical-modelling-population Postdoctoral positions at Purdue University
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that informs policy and improves medication access for historically underserved populations. Fellows will be mentored by Dr. John Allen and work within a collaborative, interdisciplinary team aligned with
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Sequencing (GBS), Whole Genome Sequencing (WGS) and targeted genotyping chips (e.g. MassArray) and analyze them together with environmental data using population genetics and machine learning tools
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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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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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health. We’ve led pioneering genetic and gene-environment interaction studies, including some of the first genome-wide association studies of depression risk in non-European ancestry populations. We’re
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management. Requisite skills include DNA extractions (ideally from noninvasive sources), PCR, sequencing and basic statistical modeling (e.g., simple regression). Desired skills include qPCR, ddPCR, and/or
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effort on active research projects and publish and present research results. Research work will focus on Computation Fluid Dynamics (CFD) models involving multiphase reacting flow simulations with emphasis
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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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discussions for other timelines are possible. Qualifications: PhD in a broadly related field (e.g., cognitive science, computer science, psychology, learning sciences, linguistics, speech-language-hearing