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developing advanced AI/ML models for applications in physics, chemistry, or materials science Experience with periodic simulation codes such as VASP Proficiency in Python programming Excellent written and oral
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completed within the last 0-5 years)in chemical engineering, materials science, industrial engineering, or related fields. Knowledge of Python, JavaScript, Microsoft Excel and other computer programming
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Experience with one or more programming or analysis tools such as Python, MATLAB, LabVIEW, or similar platforms Demonstrated ability to design and execute independent research Strong written and verbal
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of physical sciences, or in math, computer science, and electric engineering who have an interest in accelerator physics will also be considered. Strong programming skills. Proficiency in the Python programming
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learning, or optimization Strong programming skills in Python and experience with scientific computing and machine-learning libraries Ability to work across experimental, robotic, and computational systems
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languages such as R or Python. Job Family Postdoctoral Job Profile Postdoctoral Appointee Worker Type Long-Term (Fixed Term) Time Type Full time The expected hiring range for this position is $72,879.00
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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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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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-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