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genetically diverse mice under a multitude of conditions, and (3) develop multimodal machine learning models and methods to determine signatures and biomarkers to understand mechanisms distinguishing
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skills, including generalized linear models, multiple machine‑learning algorithms, MOFA and multi‑omics pathway analysis. · Strong background in experimental design, quantitative data analysis, and
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Skills/Qualifications A Bachelor Degree or an equivalent in Computer Science, Telecommunication Engineering, or a related field with a strong academic background in Machine learning, Natural
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 13 days ago
-series. Experience exploring machine learning and deep learning techniques for geospatial applications is highly desirable to effectively engage with Earth observation foundation models. Technical
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comprehensive and competitive medical and dental care programs, generous retirement benefits, and a wide array of family-friendly and cultural programs to eligible team members. Learn more at https://hr.duke.edu
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). Desirable assets are: • Machine learning, deep-learning, artificial intelligence, advanced statistical inference; • A solid record of research activities, including relevant publications in international peer
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to staff position within a Research Infrastructure? No Offer Description Activities: The post-doctoral researcher will develop machine learning models to evaluate the effectiveness and cost
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learning and deep learning. Specific Requirements PhD in acoustics. Knowledge of acoustical measurement techniques, as well as physical acoustics. Some experience in acoustic signal processing and machine
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. The successful candidate will be involved in the gravitational wave astronomy research area as part of the GRAVITY research group, within the framework of the project "Ground-based Discovery Machines
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the intersection of machine learning (ML) and the sounds of wildlife (“bioacoustics”). We are also happy to consider candidates in one of the two fields who can demonstrate a strong basis for working in this cross