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geothermal resources, reservoir modeling, techno-economic analysis and machine learning implementation, and other emerging geothermal energy-related topics. The selectee will be expected to develop funding and
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and aptitude to learn configuration and debugging of modems, dataloggers, seismic sensors, and GNSS dataloggers. Good mechanical skills and willingness to learn seismic station maintenance and
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includes: 100% employer-paid basic medical coverage Retirement contributions Paid vacation and sick time Paid holidays Please visit our Human Resources (HR) website to learn more about the total benefits
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Strong interest in pursuing a Ph.D. in a related discipline. Proficiency in programming languages such as Python (Preferred) or R. Experience in data analysis, machine learning, deep learning and
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-learning algorithms specifically designed for network optimization and security challenges. Through rigorous real-world simulation scenarios, we aim to deliver robust solutions that excel in environments
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machine learning implementation, and techno-economics. Responsibilities Research Writing Proposal Development Various other duties as assigned Required Qualifications The ideal candidate must have: Ph.D. in
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research. Capacity to develop machine learning algorithms to increase analytical efficiency. Knowledge of environmental impacts (ecosystems and air quality) of wildland fires and responses to prescribed
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, laboratory, and field environments. The degree must have been received within 3 years from the date of application. Preferred Qualifications Familiarity with machine learning (ML) and artificial intelligence
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will perform research within the Center for Generative Artificial Intelligence and its parent organization, the Machine Learning Laboratory. Successful candidates will be appointed within the Department
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learning techniques. If you meet the qualifications and are passionate about advancing our understanding of urban climate dynamics and their impacts on extreme weather events, we encourage you to apply