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Field
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impact assessment, or a closely related field. Required Knowledge, Skills, and Abilities Strong analytical and quantitative skills, including statistical programming (e.g., R, Python, or similar
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mathematical foundation and programming skills in languages such as Python, Java, Julia, MATLAB, R, and/or C++. Expertise in one or more of the following: machine learning, deep learning, HPC, Docker/Singularity
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Computer Science, AI, Machine Learning, Computer Engineer or a related field. Strong background in machine learning and machine learning frameworks Proficiency in Python and deep learning frameworks A combination of
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software as indicated in application materials. Experience with data analysis in R and/or Python as indicated in application materials. Experience working with AEM surveys of unconsolidated aquifers as
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learning methods Strong programming skills in Python and/or R Experience with deep learning frameworks (PyTorch or TensorFlow) Knowledge, Skills and Attitudes: Snakemake pipeline development with Conda
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learning and AI methods are preferred Strong skills in R and/or Python. An interest in conceiving and designing new projects, in line with the groups’ research focuses. A proven track record showing
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. Proficiency in scientific programming (e.g., Python, Fortran) for data processing, model development, and computational analysis. What You Need to Know Salary: Compensation for this position is commensurate
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field. Hands-on experience with free-space optical alignment, THz beam delivery, electro-optic sampling, polarization optics and imaging, or time-resolved pump-probe experiments. Proficiency in Python
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programming languages such as Python, Go etc. Ability to model Argonne’s core values of impact, safety, respect, integrity, and teamwork. Interpersonal skills, oral and written communication skills, and ability
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to meet these eligibility requirements will not be considered. Applicants should have experience in performing statistical and bioinformatic analyses using the R/Python programming languages. Experience