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Field
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a related field, and should demonstrate strong expertise in at least two of the following areas: Large-deformation numerical modeling (e.g., Coupled Eulerian-Lagrangian (CEL), Material Point Method
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the boundaries of cellular reprogramming by introducing scalable computational methods that streamline the discovery of reprogramming targets and control strategies. A key innovation of EdgeCR is its
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particular focus on tasks related to AI-enhanced image reconstruction, and support NOVO staff working on numerical aspects with experimental insights. The candidate will collaborate with national and
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. The position focuses on frequency-domain electromagnetic (FEM) and transient electromagnetic (TEM) methods. The successful candidate will contribute to the development of an inversion framework for the joint
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., omics or clinical data), using statistical methods, pathway/network analysis or machine learning. The candidate will conduct integrative analyses of biomedical datasets, with a focus on omics data
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of the fastest-growing academic health centers in the nation, Texas A&M Health encompasses five colleges and numerous centers and institutes working together to improve health through transformative education
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live in. Your role Research related to the following areas: Mathematical statistics, Machine Learning, High-dimensional statistics, Robust estimation methods, Probabilistic foundations of mathematical
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theory and numerical methods, with experience in HPC programming (e.g., C++, Python, MPI, OpenMP, CUDA) and parallel computing environments. - Experience in performance analysis, debugging, and deployment
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that prepare students for traditional careers in Physics. We also offer more flexible programs leading to the BA and the BS in Applied Physics (BSAP) that can result in careers in numerous professions including
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optogenetics, light-controlled gene expression systems, and photoreceptors. Familiarity with metabolic modeling (e.g., COBRA methods), genome-scale modeling, or flux balance analysis. Experience with Raman