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geoscientific process models, as demonstrated by presentations, publications and/or repositories Expertise in applying Bayesian statistical methods, machine learning methods, or related statistical inference
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therapeutics and antimicrobial peptides. The Postdoctoral Researcher will apply computational modeling, structural analysis, and machine learning approaches to support mechanistic studies of cellular signaling
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or machine learning is highly desirable Prior experience with liquid biopsy work is welcome but not required Proven ability to think creatively, work collaboratively, and communicate effectively Fluency in
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of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI implementation. Ability to apply AI to interdisciplinary research or developing AI models
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assigned as needed. The ILS Lab develops innovative methods at the intersection of operations research, artificial intelligence, and machine learning to solve complex supply chain, logistics, and
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National Aeronautics and Space Administration (NASA) | Hampton, Virginia | United States | 17 days ago
the computational work. Researchers in the group have experience with crystal plasticity using finite element and fast Fourier transform methods, fatigue indicator parameters, process modeling and machine learning
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. • Expertise in one or more of the following areas: statistical analysis of large data sets, machine learning, data visualization, and a high level of independence with a publication record to support these
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). Experience in the application and development of computational methods/tools or machine learning algorithms. Good computer programming skills in R/Matlab/PerlPython. Knowledge of basic molecular biology
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analysis. ● Prior work on kinase or other signaling-protein conformational dynamics, phosphorylation-driven activation, or allosteric regulation. ● Familiarity with machine learning and deep learning
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skills, including generalized linear models, multiple machine‑learning algorithms, MOFA and multi‑omics pathway analysis. · Strong background in experimental design, quantitative data analysis, and