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experience (generally 5 years or longer) in atmospheric sciences; and Knowledge of Fortran, Python, R, Database (Postgres, MySQL, SQLite), Shell program language skills. Preferred Qualifications: Knowledge
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related assistive technology software/apps and devices (e.g., text-to-speech programs, screen readers, magnification applications, and annotation tools) and their use on multiple devices. Provides technical
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, data mining, machine learning, natural language processing, human-centered computing, mobile and ubiquitous computing, cyber-physical systems, and engineering education. IST hosts the ABET-accredited BS
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Department: Enterprise Risk Management Classification: Program Admin Specialist 1 Job Category: Classified Staff Job Type: Full-Time Work Schedule: Full-time (1.0 FTE, 40 hrs/wk) Location: Fairfax
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Intelligence/Machine Learning (AI/ML) methods in agriculture (Agro-AI/ML); and Experience in programming with multiple languages (e.g., Java, C/C++, Python) for geospatial information systems, agro-informatic
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the globe for career success in business and government. Its research-based faculty and focus on multi-disciplinary academic programs, inclusive entrepreneurship, modular education, experiential learning, and
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Accelerator budgets and expenditures with the College of Science; Pursues funding opportunities that will increase the capacity of the Accelerator; Manages the LA (Learning Assistants) program; Supervises
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organizations in furtherance of the mission of the university. The department delivers a comprehensive program in law enforcement to provide the highest level of safety, security, and service for the students
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student-athletes across 22 NCAA Division I programs. As a distinguished member of the Atlantic 10 Conference, our teams have earned 17 conference championships, captured NCAA titles in Women’s Soccer and
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teaching licensure areas to supervise teacher candidates completing internships as part of Mason’s licensure programs. Mason is seeking individuals with licensed teaching experience in the areas of early