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computer modelling systems such as finite element analysis (FEA),. Familiarity with data analytics, machine learning, digital twin knowledge, or Python programming language. Knowledge of additive
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, adaptive control) Experience applying machine learning/AI to engineering systems Proficiency in programming and simulation tools such as Python, MATLAB/Simulink, and/or ML frameworks (TensorFlow
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programming in Python, GEE, or R, and working with modern scientific computing and/or AI/ML frameworks. Experience with analyzing large, heterogeneous environmental, geospatial, remote-sensing, or
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relations) Demonstrated strength in quantitative methods and programming (e.g., Python or R; reproducible workflows; version control) Experience or interest in AI/ML application to ecophysiological
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physics, diffusion, sorption, phase behavior, or nonequilibrium processing. Quantitative modeling or computational analysis of scattering, spectroscopy, imaging, or transport data. Scientific programming
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operations; intelligent transportation systems. Proficiency in Python and experience with at least one additional programming, modeling, or data-analysis environment such as C++, MATLAB or Simulink