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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 19 days ago
. Description: Under the guidance of a mentor, the participant will engage in a NASA-aligned research project advancing data-driven approaches to characterize wildfire risk and post-fire vegetation recovery
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, machine learning engineers, and clinical collaborators to design, implement, and validate innovative algorithms. Conducts exploratory data analysis to extract meaningful insights from complex datasets
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and analyzing multidimensional data sets Familiarity with bioinformatic and biostatistical approaches for the analysis of sequencing and proteomic data Desire to conduct team-based science in close
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research associate to advance the analysis, quality assurance, and calibration of automated pavement condition data and pavement performance modeling. The successful candidate will contribute to two
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. Experimental work and data analysis (70%) 2. Scientific writing, figure preparation (20%) 3. Collaborative work and teaching within the research team (10%) Application: Interested candidates should submit i) a
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is expected to contribute to foundational research in dynamic modeling, stability analysis, and control of coupled data center–grid systems. Emphasis will be placed on developing new theoretical
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Computational Sciences or similar. You have strong expertise on analyses of biology-related large datasets. Expertise in single-cell and spatial data analysis, spatial statistics and annotation is an advantage
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caregivers. The primary focus of this role is to support the development of digital programme content and undertake a range of research activities, including data collection and analysis, conducting
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Computational Postdoctoral Researcher - Bacterial Genomics, Transcriptomics, and Single-Cell Genomic
. • Strong computational and programming skills (Python, R, Linux, and high-performance computing environments). • Demonstrated experience in genomics data analysis, evidenced by peer-reviewed publications
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theory, analysis of Roman commissioning and early GBTDS data, support for event-analysis and planet occurrence-rate pipelines, and the publication of scientific results based on Roman exoplanet data