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candidate. The postdoctoral associate will be encouraged to take intellectual ownership of one or more projects, develop new research directions, publish at leading NLP and machine learning venues, and
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skills (Python, R, or similar) and experience building or maintaining analysis pipelines Experience with RNA-seq, single-cell genomics, and/or proteomics data Familiarity with machine learning or LLM-based
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Position Description Duke University invites applications for a Postdoctoral Associate position in Statistical Science under the mentorship of Professor Eric Laber. This position will be involved
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to simulations on quantum simulators and computers, and applications of machine learning, including neural quantum states. Candidates will benefit from state of the art computing resources at the Argonne
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. The ideal candidate will possess not only a deep conceptual understanding of neuroscience but also advanced technical expertise in machine learning, artificial intelligence, and data modeling approaches. We
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be responsible for designing and implementing physics-informed machine learning strategies for identifying constitutive laws in granular media. This includes the development of thermodynamically
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and Ni and with energy densities exceeding LMFP and competitive with NMC. A postdoctoral research position is now available on this 3D-CAT project in the area of computer modelling and materials design
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observational data of non-CO2 greenhouse and ozone-depleting gases (e.g., N2 O, CFCs, HFCs), and to extract diagnostic insights from instrument performance indicators, using machine learning methods. Additional
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quantitative, experimental, and computational approaches, leveraging powerful machine learning algorithms and extensive characterisation techniques. This research project will be carried out at University
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Join us in designing stable materials for sustainable energy devices with machine-learning-accelerated simulation and modeling. Work assignments The postdoctoral researcher will develop machine