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(HPC), or large-scale data analysis. Experience in applying AI/ML techniques to hydrological and Earth sciences. Proficiency in scientific programming languages such as Python, Julia, R, Fortran, or C/C
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reasoning or tool-augmented LLMs, RL (RLHF/RLAIF/online RL), or foundation models for science, Software engineering skills (Python) and experience with modern DL stacks (PyTorch) and multi-GPU training
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electronics. Experience in C/C++, Matlab, and Python programming. Experience in power systems software like PSCAD, PSS/e. Preferred Qualifications: Experience in real-time simulation hardware like Opal-RT and
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. Knowledge of Python programming language. Preferred Qualifications: Experience with object-oriented programming languages (especially C++), version control system (Git) and software development practices
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testing data. Knowledge of scientific software in python (numpy, scipy, pandas) or related data analysis suite. Record of productive and creative research as demonstrated by publications and conference
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, optical or electrical engineering, or a related discipline. Expertise in optical fiber communications and sensing. Proficiency in Python, C/C++, or other language for data analysis or instrumentation
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degree in physics or related discipline completed within the last five years. Preferred Qualifications: Experience with modern programming languages, particularly Python. Demonstrated ability
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salt breeders) is a plus. Experience in the analysis of heat transfer systems. Working knowledge of computer languages such as C++, FORTRAN, or Python. Experience with computer aided design (CAD
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in Python, with experience in PyTorch, TensorFlow, and common ML libraries (e.g., scikit-learn, pandas). Publication record in peer-reviewed journals or top-tier AI/NLP/ML conferences. Strong
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background in scientific data visualization, uncertainty quantification, AI/ML, statistics or a related field. Proficiency in Python and C++ programming languages. Excellent written and oral