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physiology is an asset Experience in statistics and data analysis of large data sets (including time series analyses and machine learning) Good programming skills Very good communication and interpersonal
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by Dr. Tim Pleskac (cognitive and decision modeling) and Dr. David Crandall (computer vision and AI). The postdoc will lead the development, integration, and testing of computational models of decision
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systems at various scales, for example using ab initio electronic structure methods like density-functional theory, developing interatomic potentials with various methodologies including machine learning
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Join and help us to derive global forest biomass data from the European Space Agency’s Biomass satellite mission. If you have interests in remote sensing, machine learning and forests, this is the
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tools for the design, analysis and evaluation of socially intelligent systems that aim to collaborate with humans in learning and decision-making tasks, often with the aim of improving health. Visit https
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of the postdoctoral scholars. https://postdoc.ucsd.edu/postdocs/px-contract.html Qualifications Basic qualifications (required at time of application) Doctorate degree or equivalent terminal degree in Engineering
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monitoring. Familiarity with computational image analysis, scripting (Python, MATLAB), or machine learning–based image workflows. Experience with method development, imaging assay optimization, or pipeline
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 hours ago
as one of the nation’s top public universities . Known for its beautiful campus, world-class medical care, commitment to the arts and top athletic programs, Carolina is an ideal place to teach, work
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members have been working on statistics learning, granular computing and knowledge discovery, machine learning, deep learning, and specifically interpretable artificial intelligence. Many innovative
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École nationale des ponts et chaussées | Champs sur Marne, le de France | France | about 2 months ago
specimens. The postdoc will contribute to the development of hybrid modeling and identification approaches that combine classical constitutive frameworks, numerical simulation, and machine learning. The work