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-aware multi-modal deep learning (DL) methods. At Argonne, we are developing physics-aware DL models for scientific data analysis, autonomous experiments and instrument tuning. By incorporating prior
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communication skills. Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork. Preferred skills and qualifications: Experience with MPI and other communication libraries
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, written, and oral communication skills. Ability to model Argonne’s Core Values: Impact, Safety, Respect, Integrity, and Teamwork. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long
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of chemical synthesis and characterization techniques Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker
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Energy Systems and Infrastructure Analysis Division. We are seeking applicants with a strong technical background and expertise in international trade modeling, particularly in the upstream automotive
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The Environmental Science Division at Argonne National Laboratory is seeking a postdoctoral researcher to join a project aimed at improving model representations of carbon cycling and greenhouse gas
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) Proficiency in programming languages such as Python or C++ Experience with AI frameworks like PyTorch or TensorFlow Strong communication skills and ability to work in a team environment Ability to model
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learning methods and frameworks especially applied to physical science problems. Experience with x-ray data analysis and/or modeling, such as crystallography, diffraction, or spectroscopy data analysis and
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models, including training, fine-tuning and inferencing, at scale. It will help us better understand and improve DAOS to meet the needs of AI-driven science applications. We expect the postdoc to help
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., transient absorption and emission), including laser operation, optical alignment, detector interfacing, and data analysis Excellent written and verbal communication skills Ability to model Argonne’s core