50 programming-"https:"-"https:"-"https:"-"BioData" Postdoctoral positions at Argonne
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: Contributes technical expertise through analysis and support for programs and projects associated with machine learning, HPC, and computational problems related to earth system science and other dynamical
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, ptychography, Laue microdiffraction, or related coherent/imaging techniques. Proven ability to design, conduct, and analyze complex synchrotron experiments. Proficiency in scientific programming (Python, MATLAB
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using Python, MATLAB, or equivalent programming languages. Preferred Qualifications • Working knowledge of X-ray optics, detector systems, and beamline instrumentation. • Background knowledge in ultrafast
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experience in economic and supply chain analysis, computational modeling, or policy analysis. Proficiency in scientific programming languages (e.g., Python, R) and data analysis libraries (e.g., pandas, NumPy
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programming language and contributions to open-source scientific software Good scientific productivity, as demonstrated by publications and conference presentations Effective oral and written communication
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barotropic/baroclinic ocean processes, tides, storm surge, and coastal inundation. Proficiency in scientific programming (Fortran/C/C++), Python-based analysis, version control (Git), and working in Linux/HPC
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physics, etc. Proficiency in Python or other scientific programming languages. Programming skills in numerical methods for image processing and AI/ML methods for quality improvement are advantageous
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Interaction, or a related field Strong background in scientific visualization, visual analytics, or interactive data exploration Experience programming in one or more languages such as Python, C/C
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programming, interfacing hardware, and developing machine-learning methods highly desirable. The researcher will join an Argonne funded project with interdisciplinary team of material scientists, computer
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experience in economic and supply chain analysis, computational modeling, or policy analysis. Proficiency in scientific programming languages (e.g., Python, R) and data analysis libraries (e.g., pandas, NumPy