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are proficiency in Python, deep learning frameworks such as Keras, PyTorch, TensorFlow, or other related software stacks, and a solid background in machine learning, cybersecurity, or AI robotics, and the ability
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skills, e.g. Python and/or a major language in the C family, are required. Familiarity and/or strong interest in mastering deep learning is essential. The position is based in Utica, NY. Job
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in programming (Fortran, Python), and evidence of working well as part of a multidisciplinary research team. You must possess the organisational skills and initiative to conduct independent research
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, including ability to prioritise workload and work to deadlines. Desirable criteria Scripting skills and experience in one or more open-source languages (e.g. Python, R) Prior experience/knowledge of cannabis
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or particle physics at high or medium energy. Very good knowledge and programming skills in C/C++ (or possibly Python). Good knowledge of CERN-ROOT data analysis packages. Knowledge of statistical data analysis
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experience in AI; - Advanced programming skills (e.g., Python, Java, and C++); - Ability to work well in a team and fluency (written and oral) in English. About the scholarship: 24-month contract (renewable
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, gradient coil design, etc. programming skills with MATLAB, C/C++ or Python skills and experience in manufacturing methods, such as 3-D printing experience in MRI image reconstruction (nonuniform FFT
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computational semantics models, word sense disambiguation, or semantic change detection Proficiency in Python and relevant NLP libraries Experience working with large-scale corpora or annotation pipelines Strong
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | about 8 hours ago
Countries will not be accepted at this time, unless they are Legal Permanent Residents of the United States. A complete list of Designated Countries can be found at: https://www.nasa.gov/oiir/export-control
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, Computer Science, Image Analysis, or another quantitative discipline. Achieved proficiency in statistical programming (e.g., R or Python) and familiarity with advanced analytical techniques (e.g., causal inference