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structure, catalytic properties, and reaction mechanisms Demonstrated experience in spectroscopy simulations, including XANES, EXAFS, and Mössbauer spectroscopy Proficiency in Python and relevant
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programming and data analysis (Python, MATLAB, or equivalent). Experience with machine learning, data-driven modeling, or AI methods applied to physical sciences datasets. Familiarity with handling and
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, surrogate modeling, clustering, anomaly detection, or probabilistic modeling. Proficiency in Python/Julia/R and scientific computing/data analysis tools and related libraries. Experience working with large
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, engineering, computational science, a physical science (materials science, chemistry, physics etc.), or related field. Hands-on experience with AI frameworks and employing large language models. Strong Python
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acquisition, instrument control, and data analysis in Python or similar languages Knowledge of quantum optics measurements such as photon correlation functions or photon-number-resolved detection Familiarity
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linear, mixed-integer, and stochastic programming. Work with programming languages such as Python, Julia, or C++ to build robust analytical tools and perform large-scale data analysis. Collaborate with
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deep learning including data collection, architecture development, model training, and validation Interest in software development, with particular emphasis on the Python programming language and
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physics or a closely related field with 2+ years of postdoctoral experience. Strong programming skills, with demonstrated proficiency in Python. Experience applying machine learning techniques
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-completed PhD (within the last 0-5 years) in field of physics, engineering, or a closely related field Demonstrated programming proficiency in C/C++, Python, or another scientific programming language
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Science, Chemistry, Chemical Engineering, Electrical Engineering, Computer Science, Physics, or a related field Demonstrated proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow