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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 1 hour ago
to constrain the representation of aerosols in the NASA GEOS Earth System Model. Activities that would be involved in this project include (but are not limited to): Implement machine learning transfer learning
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with causal inference methods or machine learning approaches Demonstrated experience in scientific writing and publication Ideal for candidates who: Have recently completed (or are near completion of) a
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at the interface of biostatistics, machine learning, and biomedical data science. This mentored postdoctoral position is designed to support the development of an independent research trajectory in methodological
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(HIMS), in close collaboration with industrial partner BOR-LYTE and Smart Industry testbeds. This position offers a unique opportunity to combine inorganic chemistry, spectroscopy, machine learning, and
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include an FC150 bump-bonding machine, a Pac Tech SB2 solder deposition machine, an F&K Delvotec automatic wire bonding machine, and a dedicated lead-shielded room for sensor characterization with radiation
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knowledge and proven capacity of data analytics and machine learning. *Excellent programming in Python, R, SQL. Have experience with tools such as Google analytics, AWS, Looker, Tableau, or similar
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that combines modern machine learning approaches with large-scale biological data to automate genome curation by detecting, interpreting, and correcting structural errors, reducing manual effort from weeks
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. Emphasis is placed on artificial intelligence/machine learning approaches applied to digital data and multi-omics data. Additional responsibilities include mentoring students, collaborating with faculty
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new insights into the phenomena observed and enrich the databases required for deep learning methods. The neural networks currently being developed at LISTIC to detect and segment areas of movement in
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the project based on your interests and in collaboration with a leading architectural firm. The candidate is expected to publish in leading Human-Computer Interaction venues. Your competencies You hold a PhD