678 machine-learning-"https:"-"https:"-"https:"-"https:"-"RAEGE-Az" Postdoctoral positions in United States
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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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in Machine Learning, Computer Science, Electrical Engineering, Geophysics, Applied Mathematics, or a closely related field. Demonstrated strong research skills, evidenced by high-quality publications
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of natural language processing, machine learning, artificial intelligence, and human-computer interaction. Established within the School of Computer Science, LTI pioneers innovative approaches to understanding
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. Experience working with a high-performance computing (HPC) environment. Familiarity with machine learning and advanced statistics. Experience with analysis of time series data from intracranial EEG (iEEG
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to effective therapeutic strategies targeting IDPs Collaborate on the development of open-source machine learning tools to support these therapeutic designs Work closely with high-throughput screening teams
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Research Associate will contribute to developing and/or applying artificial intelligence, machine learning, and image segmentation and/or data science-based methods to address cutting-edge topics, including
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Infrastructure Sciences Division. Machine learning (ML), specifically deep learning (DL), has been demonstrated to successfully predict the weather for 1-14 days with skill on par with numerical weather prediction
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and great opportunity of interdisciplinary training in machine learning and functional genomics. The project combines cutting-edge computational approaches, especially state-of-the-art machine learning
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candidates with a proven track record in developing open-source machine learning, deep learning, or cheminformatics tools (Preferred written in Python). Job Duties Plans, directs and conducts research
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of computational biology, Genomics, machine learning, and data science, contributing to the development and evaluation of advanced algorithms for analyzing large-scale biological datasets. This role is ideal