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). • Demonstrated experience writing SQL queries. • Demonstrated experience with programming languages (e.g., SAS, Python, or R). Preferred Qualifications • Bachelor’s degree. • Three (3) years of relevant experience
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for model accuracy across multiple scenarios, including safety and risk assessment, and performance with real-world simulations. Ensure compliance of all LLM model architecture with ethics, privacy, and data
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Lawrence Berkeley National Laboratory has multiple openings for a Scientific Engineering Associate in Berkeley, CA. Duties: Perform scientific data analysis using the scientific python stack
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California State University, San Bernardino | San Bernardino, California | United States | about 24 hours ago
database support in a multiple hardware platform and operating system environment. - Ability to work and communicate with users to define and meet database needs and requirements. Preferred Qualifications
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programming language, such as Python. Knowledge of AI, Machine Learning, and Deep Learning techniques and frameworks. Thorough knowledge of technical development best practices and resourcing, sufficient
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systems, application issues, and network connectivity problems. Proven experience in PowerShell scripting or other scripting languages (e.g., Python, VBScript) to automate and streamline system
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. - General knowledge of network configuration, programming, and protocols. - Ability to provide database support in a multiple hardware platform and operating system environment. - Ability to work and
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/spectroscopic, optical), calibration and data-processing, in-orbit commissioning and performance verification Experience with programming (Python) Experience in the development of optical and infrared scientific
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. Basic programming skills (e.g., MATLAB, Python) for data handling and sensor signal analysis. Enthusiasm for interdisciplinary research and the ability to support multiple concurrent projects. The terms
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for integrated sensing and communication (ISAC). Responsibilities: Lead the design, setup, and execution of ISAC channel measurement campaigns across multiple environments, hardware platforms, and frequency bands