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care vision would involve the merging of technological advancements in several threads computing, imaging, and information technology; health care practice; and health care technology. We are interested
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based on the following topics of interest: Relationships between powder characteristics, process metrics, and final part quality. In-process machine-vision applications for real-time assessment of powder
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tested in the research community which include highly novel methods such as melt pool emission thermography or spectroscopy, structured light projection or other machine vision applications, acoustic
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controls. The position will require programming skills, mostly with Python. To understand the vision of beamline operations inspiring this opportunity, see these two recent publications: https://doi.org
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://jarvis.nist.gov/) infrastructure uses a variety of methods such as density functional theory, graph neural networks, computer vision, classical force field, and natural language processing. We are currently
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[3]. [ 1] OpenAI Microscope, a collection of visualizations of every significant layer and neuron of 13 important vision models, URL [ 2] Peter Bajcsy et al., “AI Model Utilization Measurements
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parallel algorithms, execution of algorithms in the computer cloud, to delivering on-demand measurements over the Web. key words Image processing; Machine learning, Computer vision; Statistical methods
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computer vision and machine learning. Our computational methods development has three primary goals. The first goal is continued support of expert-driven biomolecular structure determination by NMR, with