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of scientific principles and theories. Maintains substantial knowledge of state-of-the-art principles and theories. Develops advanced analytical models and systems and provides solutions and analyses
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Associate Research Scientist / Post-Doctoral Associate in the Division of Science (Computer Science)
include: Strong foundation in one of the following areas: Machine Learning / Information Retrieval / Knowledge Graph Representation / Recommender Systems Graph Theory/Network Science Python, and up-to-date
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: Complete knowledge of all job functions and the broad industry best practices, techniques and standards. Ability to transfer knowledge and application of complex principles, theories and concepts to peers
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Associate position in the broad research areas of non-associative algebras and representation theory. Although all applicants with a background in these two areas will be considered, priority will be given
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of this project. The candidate’s background can be either in in traditional music analysis (with a PhD in musicology, music analysis or music theory) and/or in computational musicology, digital humanities
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of extra-chromosomal DNA in human cancers. The position is funded for initially two years (with options of extension) by the CRUK and NCI Cancer Grand Challenge to work on the evolutionary theory and
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Infrastructure? No Offer Description A two-year post-doctoral position is open at the Interdisciplinary Research Institute of Grenoble (IRIG) of the CEA Grenoble (France) on the theory and modeling of silicon
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of student researchers What you contribute Ph.D. in Electrical and Computer Engineering, Computer Science or related program Background in Information Theory, ideally with significant prior publications in
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) Theoretical Modeling: Develop and refine models for entanglement harvesting using continuous-variable quantum information theory and Gaussian quantum states steering. (2) Experimental Simulation: Simulate
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rigorous methodologies, theory-driven insights, and empirically grounded research. The social scientific research conducted by CRISES will inform the vision and attainment of a world without invidious social