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Field
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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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-environment-climate public goods (AECPG). By combining insights from results-based, collective and spatially targeted schemes with novel financing and robust monitoring, REWARD seeks to build scalable models
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 19 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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other field or laboratory instrumentation Apply appropriate behavioral, statistical, econometric, causal, spatial, machine learning, deep learning, computer vision, time-series, or mixed-methods
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, viability and biological function. The work will require rigorous experimental design, appropriate controls and benchmarks, statistical analysis, traceable data and predefined acceptance criteria. The role
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-generation sequencing and single-cell technologies (e.g., scRNA-seq, scATAC-seq, scTR-seq, and/or spatial transcriptomics). Previous experience in both Bioinformatics/Genomics and Cancer Biology is desirable
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in computational methods and/or quantitative methods, primarily spatial analysis. Experience in supervising and managing research groups. Experience in conducting academic research related to analyzing
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, Spatial data analysis or GIS Whole-genome sequencing, phylogenetics, or phylodynamics Data management and reproducible analytical workflows Quantitative modeling and statistical inference. Applicants
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large spatial and temporal scales. Experience in the conceptualisation and development of new methodological approaches for analysing and modelling species range dynamics, functional trait variation
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and damaging storms, and cascading risks such as bark-beetle outbreaks. Forest owners and regional authorities need spatially detailed, timely information on where climate stress is emerging, and which