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and apply machine learning and deep learning models to analyse complex, multi-dimensional datasets, including spatial transcriptomic, proteomic, and single-cell sequencing data. The candidate will
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, fieldwork, data processing, reporting and project administration. The successful candidate will be proficient in applying integrated spatial analysis techniques to coastal and marine environmental data
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evaluation framework covering statistical fidelity, temporal and spatial structure, physical plausibility and downstream task performance (e.g. train-synthetic-test-real forecasting). You will collaborate with
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 3 hours ago
measurements. The participant will research and develop robust metrology methodologies to characterize mirror surface quality across multiple spatial frequency ranges using techniques such as Fizeau
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appointment. Candidate’s CV must state qualifications or if pending upon submission. Preferred Qualifications: Proven experience analyzing scRNA-seq, scATAC-seq, spatial-RNA-seq or other genomic data. Proven
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Emirates Nature–WWF, the successful candidate will contribute to marine habitat mapping, spatial analysis, and environmental data integration to support fisheries management and marine conservation
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, document, archive, and transfer large datasets; maintain metadata, geographic crosswalks, and version control. Formal Analysis - Apply statistical, spatial (e.g., nearest-neighbor distance, Moran’s I), and
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data with long-term demographic datasets (e.g., ForestGEO data) Spatial analysis and ecological modeling (neighborhood models, density dependence, spatial statistic Experience with whole-genome
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bioinformatics, particularly single‑cell RNA‑seq, multi‑omics, and spatial transcriptomics analysis. Specific Requirements Proficiency in Python and R; familiarity with common bioinformatics tools and pipelines
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-to-office data integration. Experience creating maps, dashboards, reports, and spatial analysis products for operational decision-making. CAD experience, especially with facilities, utilities, infrastructure