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Field
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analysis, data organization and quality control, software testing, visualization of research data, scientific documentation, and general laboratory research support while working collaboratively with a
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Advance Computational Behavioral Analysis Develop and validate automated methods for analyzing caregiver-child interactions using computer vision, multimodal machine learning, and artificial intelligence
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, the fellow will lead the development and execution of advanced functional and distributional data analysis techniques. This role requires independent analytical acumen to design simulation studies, process
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. Excellent analytical skills with high attention to detail. Experience with geospatial data visualization tools such as ArcGIS, Cesium, or similar. Familiarity with urban-scale building energy modeling
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malaria parasites or other infectious disease models. Proficiency in FlowJo, R, and/or RStudio for high-dimensional flow cytometry data analysis and visualization. Experience with high-parameter spectral
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projects. The research associate will develop expertise in retinal imaging, experimental design, data analysis, scientific writing, manuscript preparation, and presentation of research findings, supporting
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University of California, Los Angeles | Los Angeles, California | United States | about 21 hours ago
activities may include analysis of whole-genome and next-generation sequencing data (including quality control, variant calling, annotation, filtering, genetic association, and biological interpretation
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Candidates with experience in flow cytometry, single-cell analysis, quantitative imaging, and routine use of R or Python for data analysis and visualization will be especially competitive. The ideal candidate
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 hours ago
programming (Python, MATLAB, IDL) with experience in data analysis, visualization, optical raytracing, and simulation software. Ability to develop custom analysis tools. Knowledge of numerical methods
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spectrometry-based proteomics, including data deposition and retrieval through the PRIDE (Proteomics Identifications) database, and in bioinformatic data analysis, including pathway and ontology enrichment (ORA