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Postdoctoral Research Associate who will focus on creating innovative artificial intelligence algorithms for the trusted visualization of large-scale 3D scientific data. This position resides in the Data
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About the Opportunity Postdoctoral Research Associate – Human Data Interaction/Data Visualization – The Roux Institute, Portland, Maine We are currently seeking two postdoctoral research fellows
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Requirements Experience in machine learning or artificial intelligence applied to biomedical data Experience in integrating clinical, molecular and imaging data for translational research Publications in high
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Cornell University, History of Art and Visual Studies Position ID: Cornell-History of Art and Visual Studies-POSTDOC [#31620, WDR-00056959] Position Title: Position Type: Postdoctoral Position
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languages Hands-on experience with MD simulation tools such as NAMD, GROMACS, AMBER, or LAMMPS, and visualization tools (e.g., VMD, PyMOL) Experience working on high-performance computing (HPC) systems
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, Intelligent_Mapping is integrated into the IRIMA Plateformes Consortium, supported by BRGM (PI: J. Langlois). The primary aim of Intelligent_Mapping is to develop Artificial Intelligence (AI) algorithms able
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and software tools for visualizing and analyzing materials characterization data Develop novel, data-driven materials characterization workflows Advance understanding of process-structure-property
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Artificial Intelligence with a primary focus on Computer Vision, pattern recognition, and visual generative modeling. CVI2 offers the opportunity to contribute to a diverse portfolio of projects, including
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Postdoctoral Researcher in Natural Language Processing and Digital Humanities (18 months, full-time)
research task is to model semantic change and conceptual structure using Natural Language Processing. We will build customized NLP pipelines for premodern Greek and humanistic Latin, train and evaluate word
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(see “Partners” section below). ARKEY aims to bring added value for society and public service, by improving the accessibility and intelligibility of archives: a priority for many researchers and a