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to advanced AI, ML, xAI, and optimization for sustainable energy systems analysis and forecasting and being familiar with large language models, cloud platforms and distributed computing environments Experience
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management, cloud computing, machine learning, and algorithms for the Internet. Example topics of interest include but are not limited to the design and analysis of sketches and filters for use in real systems
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management, cloud computing, machine learning, and algorithms for the Internet. Example topics of interest include but are not limited to the design and analysis of sketches and filters for use in real systems
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(Python, JavaScript), deep neural networks and computer vision; Design and implementation of database systems; Design and implementation of application programming interfaces, server-based and cloud
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science. Practical experience in Python programming and database management. Exposure to cloud computing environments and API integration. Development of skills in machine learning and data analysis
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spectrometry data analysis or metabolomics is highly desirable Experience with cloud computing platforms and distributed computing tools Experience with deep learning architectures such as CNNs, LSTMs, and
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Retrieval and Extraction) Privacy, Safety, and Security Quantum Computing Software Engineering and Programming Languages Systems, Networking, and Cloud Computing Evaluation Criteria Applications are evaluated
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. Familiarity with cloud computing and AI frameworks. Extensive experience working on one or more areas: image processing, machine learning, time series, digital health, bio-signal processing, and wearable
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lasting impact. Review our detailed benefits information here. Explore the additional perks of working at CSU here . For the total value of CSU benefits in addition to wages, use our compensation calculator
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PyTorch, TensorFlow, and Scikit-learn. Familiarity with cloud computing and AI frameworks. Extensive experience working on one or more areas: image processing, machine learning, time series, digital health