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or prior experience with multilingual or low-resource NLP Programming skills in Python and proficiency in deep learning frameworks (e.g., PyTorch, TensorFlow) and their application in high-performance
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familiarity with supercomputing or cloud platforms. Experience with AI/deep learning beyond simple tools (e.g., Random Forest, ANN), particularly in integrating physical models and AI algorithms. Knowledge
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, cryoET, and X-ray crystallography, you should be an expert in at least one of those techniques and keen to learn the others. You also should have a deep interest in molecular mechanisms underlying
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role in the global carbon cycle by transferring carbon from the surface ocean to the deep sea through the formation, sinking, and remineralization of organic particles. Despite its importance, our
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should be an expert in at least one of those techniques and keen to learn the others. You also should have a deep interest in molecular mechanisms underlying biological processes and – if not experience
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sciences education and a deep commitment to excellence in scholarship and all forms of creative and intellectual expression, with sponsored research expenditures totaling more than $38.6M per fiscal year
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turbulent combustion applications, as well as parallel scientific computing. Knowledge of deep machine learning (using TensorFlow, PyTorch, etc.) for multi-fidelity modeling, regression tasks, management and
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with a team. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Preferred Knowledge, Skills, and Experience Experience in machine learning/deep learning methods
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bodies down to the bottom of the deep sea. The Aquatic Life Foundation Project (AqQua ) will, for the first time, combine billions of images acquired with a variety of devices across the globe for large
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. Renowned for hands-on learning and pioneering research, Mines educates future leaders in STEM fields who will make a meaningful impact on the world. Our vibrant community of supportive faculty, tenacious