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analysis, modeling, or automation using tools such as Python, MATLAB, C#, C++, or similar engineering software environments. Experience with CAD/CAM/CAE tools such as Siemens NX, SolidWorks, Mastercam
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data acquisition, data analytics, statistical modeling, and machine learning in manufacturing environment. Proficiency in Python and common data science and machine learning libraries (e.g., NumPy
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knowledge of models of strongly correlated electron systems Proficiency with scripting or programmatic languages, such as Python, c, and matlab Excellent written and oral communication skills Motivated self
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) and hyperparameter optimization or AutoML techniques. Proficiency in Python and familiarity with software engineering best practices (version control, testing, documentation). Experience with HPC
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research will involve Python scripting within the Thermo Fisher AutoScript environment to control operation of the microscope beam, stage, detectors, and spectrometers, with a particular emphasis on annular
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: Experience applying machine learning methods for predictive analysis. Expereince with the Python programming language. Experience with the creation, validation, and use of synthetic data for constructing
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Qualifications: A Ph.D. degree in electrical engineering, or related discipline completed within the last five years. Expertise in power systems and power electronics. Experience in C/C++, Matlab, and Python
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Requirements: The prospective candidate should be well-versed with deep neural networks, have experience working on PyTorch or similar DL frameworks, programming in Python (preferred), NLP packages and pipelines
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integrating these paradigms into unified compilation and optimization strategies. Programming Languages & Frameworks: Experience with Julia, Rust, Python, Kokkos, OpenSHMEM, or similar emerging ecosystem tools
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., Python or R; reproducible workflows; version control) Experience or interest in AI/ML application to ecophysiological research Preferred Qualifications: Hands-on experience with lab/growth chamber and/or