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Field
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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. Responsibilities The postdoctoral associate will – based on their research interest – contribute across one or more of the lab’s five core themes: Genomic Technology: Design and execute new, large-scale experimental
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 18 days ago
include advancing foliar trait retrieval algorithms, atmospheric correction over dense humid tropical canopies, machine learning and dimensionality reduction for handling big data, landscape evolution
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depth in some of the following areas (not all are required): Large-scale data analysis and learning analytics methods Experimental or quasi-experimental design; validity and measurement Working with LLMs
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dissemination, data cleaning and management, data analysis, experience managing a multi-year and multi-site federally funded grant, human subjects’ protocols and management, responsible conduct of research. Large
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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. Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants . This is a term position
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. Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants . This is a term position
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integrate protein biochemistry, analytical methods, molecular microbiology, and quantitative data analysis. These efforts will improve assay sensitivity, selectivity, stability, and performance in clinically