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such as SCRUM. Strong foundation in machine learning, deep learning, or computer vision Strong Python development skills and familiarity with git, CLI tooling, VS Code Proficiency with PyTorch and/or
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when applying to this position. You may upload these directly to your application or have them sent to [email protected] (For postdocs, use [email protected] ) with the position title
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connecting molecular dynamics to cellular or tissue-scale processes Experience with deep learning frameworks such as PyTorch or TensorFlow Exposure to AI-enabled scientific workflows that couple simulation
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, Pandas, SciPy, scikit-learn, PyTorch, TensorFlow) Experience developing and deploying machine learning or deep learning models Ability to present complex results to multidisciplinary teams, including
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(For postdocs, use [email protected] ) with the position title and number referenced in the subject line. Instructions to upload documents to your candidate profile: Login to your account via
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publication in relevant areas such as computer architecture, HPC, quantum computing, compilers/runtime systems, or heterogeneous computing. Special Requirements: Postdocs: Applicants cannot have received
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and approaches to solve complex problems (e.g., information retrieval/extraction, machine learning/deep learning, networking) Experience working with geospatial data and processing workflows and
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to solve complex problems including information retrieval/extraction, machine learning/deep learning, and networking Special Requirements: Export control, no clearance: This position requires access
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. Experience with developing machine-learning surrogates for structure-property relationship, generative AI models, material representations, machine learning force-fields (especially extensions to spinful
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Experience with deep learning frameworks such as PyTorch or TensorFlow Exposure to AI-enabled scientific workflows that couple simulation with data-driven modeling, including emerging approaches involving