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differences in learning, memory, and processing between these systems. This project develops the necessary methods to study how smart AI-models are compared to people, now and in the future, and sheds light on
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research teams that include faculty, graduate students, and undergraduate students. One student’s research used machine learning to solve physics problems, while another’s helped create a data science
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. Proficiency in programming languages for data analysis (e.g., Python, R) and experience with machine learning, statistical modeling, and wearable sensor data analysis is desirable. We expect you to be able
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of this project for a one-year period (100% full-time commitment) to make a significant contribution to the implementation of machine learning (ML) algorithms. The postdoc is expected to have proven experience in
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Cornell University, School of Chemical and Biomolecular Engineering Position ID: Cornell-ChemE-POSTDOC [#30598, WDR-00055411] Position Title: Position Type: Postdoctoral Position Location: Ithaca
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Malmsten) whom together with additional professors within COMMONS will guide the projects and the training of the recruited postdocs towards leading academic or industrial research positions. This post
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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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Python Arduino and C++ (Physical Computing) Creation of interactive objects and components Machine Learning and Natural Language Processing Specific Requirements Candidates must hold a PhD in engineering
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in computational methods, particularly those with backgrounds in machine learning, artificial intelligence (AI), statistics, bioinformatics, or analysis-acceleration technologies. Candidates should
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competitive ERC. The project focuses on the development of a first-principles, machine-learning-accelerated computational framework for modelling polymorphism, anharmonicity, and electron–phonon interactions in