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algorithms with mainstream programming languages such as Julia, Python, Java, C/C++, etc. Proficiency in writing scientific research articles and presenting results at academic conferences. Experience with
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algorithms and software for large-scale scientific applications. Expertise in programming in a high-level language such as R or Python. Experience and skills in interdisciplinary research involving
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-disciplinary analysis efforts, and shape a growing research program. The successful candidate will receive strong mentorship and autonomy to develop a scientific vision, build collaborations, and pursue high
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the domains of environmental, water, and energy system analysis. Prepares reports, papers, and presentations for conferences, workshops, and technical journals. Supports program development including
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) or equivalent experience in a computational science discipline, computer science, or in a related field Strong programming skills in one or more scientific programming language, such as C++ and Python Experience
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preferred. Strong data analysis skills and ability in programming languages, such as Python, for performing experiments and analyzing data. Knowledge of innovative phase retrieval algorithms is desirable
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of physical chemistry, inorganic chemistry, computational materials science, or chemical engineering or a closely related field, with demonstrated experience in the scientific application of this knowledge and
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, computational science, a physical science, or engineering or related field. Comprehensive experience programming in one or more programming languages such as Python, C/C++. Experience with one of the AI
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instrument programming. Interest in software development, in particular, expertise in C or C++ and Linux/Unix programming and Python. Familiarity with scientific productivity, as demonstrated by publications
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-aware multi-modal deep learning (DL) methods. At Argonne, we are developing physics-aware DL models for scientific data analysis, autonomous experiments and instrument tuning. By incorporating prior