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Field
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, atmospheric signals), data fusion across sensing modalities, and development of scalable machine learning pipelines. Work will be entirely computational and based in Seattle, with no field deployment
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primates or humans – Theoretical neuroscience, machine learning, or AI • Proficiency in Python, MATLAB, or equivalent data‑analysis frameworks. • A passion for big‑picture questions, open science, and
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degree in biomedical data science, computational biology, genetics, bioinformatics, machine learning, computer science, statistics, engineering, medicine, or a related field. Strong candidates may have
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Lab researches on a variety of computer systems topics including HPC resilience, data center power management, large-scale job scheduling and performance tuning, parallel storage systems and scientific
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related field Knowledge, Skills, and Abilities: Familiarity with appropriate laboratory and technical equipment; ability to effectively use a computer and applicable software to create data bases, perform
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Expertise in machine learning, including building and deploying prediction models Strong data science coding skills in programs and languages such as Python, R, Stata, and SQL Experience with research in
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
/or machine learning/artificial intelligence algorithms. Projects may also include work focused on the analysis of spatial and geographic data and work extrapolating results to different spatial scales
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embracing neurodiversity ● Skillful with computer software and statistical analysis on PC or Mac ● Must pass all criminal background checks as required by the State of Minnesota Preferred ● Demonstrable
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 months ago
to receive before the start of the position) a PhD in Computer Science or EE/ECE on a topic in machine learning applied to natural language processing, computer vision, or a related area. Strong publication
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demonstrated ability to design, train, and deploy large-scale models Expertise in at least one of computer vision, speech recognition, or multimodal learning, with experience in real-world technology deployment