102 distributed-algorithm-"Meta"-"Meta" positions at Cornell University in United States
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, developing novel algorithms for pattern detection, extreme event attribution, and seasonal forecasting. Lead development of innovative visualization techniques and interpretable machine learning methods (30
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operations following museum and university policy. Greet visitors, provide information, and answer questions; answer a multi-line telephone; log activities, distribute and track keys and access cards; maintain
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. utilizing desktop publishing software. • Assist with the preparation, distribution, proofreading and mailing of brochures, newsletters, event flyers, certificates, and other promotional materials
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that the annotation models implemented match user needs and expectations Translate findings into requirements for the engineering team to inform the algorithms, models, annotations, and ultimately the data is made
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novel algorithms for pattern detection, extreme event attribution, and seasonal forecasting. Lead development of innovative visualization techniques and interpretable machine learning methods (30%). Drive
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science, including supervising team members, developing novel algorithms for pattern detection, extreme event attribution, and seasonal forecasting. Lead development of innovative visualization techniques
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algorithm-based technologies in service occupations, with a focus on how collective bargaining and other forms of collective worker voice influence these strategies and worker outcomes. The US research will
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on available work, funding, and performance. Anticipated Division of Time (30%) Direct research program in AI/ML applications for climate science, including supervising team members, developing novel algorithms
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Systems will participate in the research efforts of developing systems integration, analysis, design, control, and/or optimization models and algorithms for smart energy systems to enable smart and healthy
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collected by volunteers. The workflows generate estimates of species’ distributions and abundance, measure how they change over time, and identify the features of the environment associated with populations