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bonding, defects, catalysis, batteries, solid-state chemistry, molecular systems, or related materials classes. Strong Python skills and familiarity with LLM APIs, agent frameworks , PyTorch, and the Python
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Experience with developing AI/ML Deep Learning models, working with agentic workflows, model training and other emerging AI techniques and tools Programming experience in Python, C++, or similar scientific
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learning frameworks such as PyTorch, TensorFlow, or JAX Experience with optimization and active-learning libraries such as BoTorch, GPyTorch, or scikit-learn Strong programming skills, especially in Python
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-throughput laboratory systems Proficiency in Python or similar programming languages for data processing, statistical analysis, and integration with AI/ML tools Excellent written and verbal communication
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, physics, computer science, and/or data science Demonstrated accomplishments in materials informatics, scientific machine learning, or AI-guided experimental design Strong Python and scientific computing
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relevant for data manipulation and analysis including experience with creating and using complex models in Simulink & scripting in Matlab, Python, R. A successful candidate must model Argonne’s Core Values
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environment. Demonstrated strong analytical and problem-solving skills. Experience in studying geological or biological systems, and tomography are beneficial. Programming expertise in Python or other
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engineering, or a related field. Strong programming skills in Python and experience developing research or production-quality machine learning software. Experience with machine learning or deep learning
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., Python, Fortran, C++) Knowledge of data analysis techniques and statistical methods Proven scientific writing and oral communication skills Ability to work both independently and collaboratively in a team
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sensing, quantum information science, superconducting circuit, or magnonics. Proficiency in scientific software development (e.g., Python, COMSOL, HFSS or similar languages). Ability to model Argonne’s core