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Field
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demand forecasting or behavior modeling Computing & Data Systems Cloud computing (AWS, Azure, GCP) Big data pipelines, distributed computing, and geospatial data processing Python, R, SQL/NoSQL
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the use of MATLAB and python Manuscript preparation and ability to communicate research results clearly Knowledge, Skills, and Abilities Ability to multitask and work cooperatively with others
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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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electronics. Experience in C/C++, Matlab, and Python programming. Experience in power systems software like PSCAD, PSS/e. Preferred Qualifications: Experience in real-time simulation hardware like Opal-RT and
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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 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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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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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