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; excellent computer skills including experience with databases (Airtable a plus); tech-savvy and interested in learning new software as needed. PREFERRED: MIT experience. Occasional weekday evening and weekend
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Program Instructor Certification. Ability to teach using methodologies that support a student-centered learning environment. Computer literacy and the ability to use computer technology in classroom/lab
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and facilities in high-performance computing, machine learning and artificial intelligence, human-system interaction, network science, sensing, large-scale structural testing, materials manufacturing
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Engineering (CSE), Bioinformatics, Quantitative Bioscience (QBioS), and Machine Learning (ML@GT). Equal Employment Opportunity The Georgia Institute of Technology (Georgia Tech) is an Equal Employment
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the student may not already have substantial computer science classwork or knowledge, the hope is they will grow and learn in the position and be able to apply their skills from their coursework in a positive
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University of North Carolina at Charlotte | Charlotte, North Carolina | United States | about 19 hours ago
and AV systems in all learning spaces at the University. This position also performs routine maintenance and room checks to test and resolve potential hardware and software issues. The position will
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collaborative and interdisciplinary activities. Job Requirements: Preferably PhD degree in Computer Engineering, Computer Science, Applied Mathematics or equivalent. Strong academic background in machine learning
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on innovation in semiconductors, biology, machine learning, and material science toward an intelligent closed-loop system of non- or minimally invasive sensors and actuators enabling personalized and periodic
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software infrastructure necessary to bring cutting-edge machine intelligence from simulation into the physical world. Key Responsibilities: • Develop, optimize, and maintain data pipelines for processing
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Engineering, we are seeking a researcher with a strong interest in developing and applying machine‑learning methods for materials design, in particular steel design. The position is part of our growing research