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to preventive interventions, decision support to implement mental health interventions, longitudinal data analysis, machine learning/NLP/AI, integrative data analysis, and related grant writing. This candidate
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National Aeronautics and Space Administration (NASA) | Fields Landing, California | United States | 16 days ago
. Description: The post-doctoral fellow will apply machine learning and/or other data science techniques to conduct scientific research, improve remote sensing data products and analysis, integrate machine
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Job Description This position offers a unique opportunity to work on advanced projects at the intersection of AI, machine learning, computer vision, and multimodal learning, focusing on advancing
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understanding of artificial intelligence applications and methodologies, such as working knowledge of generative AI tools, use of large language models, machine learning, and ethical frameworks for AI
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Qualifications Experience with Matlab, Phyton, C++ or other programming languages. Experience with remote sensing (multispectral and thermal IR). Experience with LiCOR measurements. Experience with machine
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Qualifications Experience with Matlab, Phyton, C++ or other programming languages. Experience with remote sensing (multispectral and thermal IR). Experience with LiCOR measurements. Experience with machine
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, generous retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at https://hr.duke.edu/benefits/ Duke is an Equal Opportunity Employer committed
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will develop novel statistical and machine learning methods for any of the following: multi-omics data (such as bulk and large-scale single-cell RNA sequencing data, spatial transcriptomics, bulk and
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areas: Generative AI Agentic AI Graph Representation Learning and Modeling Foundation Models Large Language Models Multimodal Learning Basic Qualifications A Ph.D. or equivalent degree in Machine Learning
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contextual modulators of executive control like emotion and motivation. We use and develop advanced computational methods, including 'big data' statistical methods, machine learning, and artificial