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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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implementations of genomic selection in canola. Imputation (20%) – Implement genotype imputation algorithms to enable joint analysis of historical datasets genotyped using different marker panels. Presentations
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learning. At least five (5) years of experience in AI/ML/DL or equivalent combination of education and experience. Demonstrated experience in algorithm development and structured programming ability
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of Mathematics at Cornell. Members of the lab engage in interdisciplinary research, drawing on approaches from geometry, topology, graphs and networks, probability/statistics, and algorithm design, in conversation
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for controlled environments with economic impact in New York State and beyond. The successful candidate will use novel methodologies, digital tools, and sensors to understand and optimize CEA crop physiology and
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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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of experience in AI/ML/DL or equivalent combination of education and experience. Demonstrated experience in algorithm development and structured programming ability. Experience in scientific programming and the
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to improved system design. The research program may focus on small scale technologies to improve production (e.g., sensors) or large-scale optimization (e.g., regional economic models) or anything in between