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Field
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Python and/or MATLAB; familiarity with numerical optimization libraries and scientific computing. Strong written and oral communication skills; ability to work independently and in teams. Position Type
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(e.g., R, SAS, Python, or similar). Equipment Used: standard research equipment such as light emitting diodes, data logger, environmental sensors, LI-COR gas exchange system, fluorometer. Part time
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operation to support design performance and flexibility. Utilize advanced simulation codes (e.g., Xsuite, MAD-X, Impact-X, TRACK, ELEGANT) and Python-based workflows to integrate and analyze results. Provide
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experiments, natural language processing, and network modeling. Experience mentoring students. Expertise in Python and TensorFlow. Proficiency in R, SQL for data analysis and visualization. Preferred
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. Proficiency in Python programming and major ML/DL frameworks (e.g., PyTorch, TensorFlow). Solid understanding of optimization and regularization methods for training complex neural networks. Practical knowledge
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experiments, natural language processing, and network modeling. Experience mentoring students. Expertise in Python and TensorFlow. Proficiency in R, SQL for data analysis and visualization. Preferred
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of appointment. The ideal candidate will demonstrate: Strong quantitative and spatial analytic skills, with proficiency in R and Python for data management, modeling, and visualization. Experience
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mathematics. Programming Skills: Proficiency in Python, TensorFlow and scikit-learn, experience in C++ Documented Productivity: Record of peer-reviewed publications Interdisciplinary Interest: Candidates should
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. Basic Qualifications: A PhD degree in civil, chemical, or environmental engineering. A minimum of 2 years of experience in the use of Python for programming of data analytical models and algorithms
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for large relational databases using SAS, R, Python and/or SQL. Demonstrated oral and written communication skills, and the ability to present scientific findings in various formats and to compose manuscripts