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Field
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receive advanced training in: Statistical genetics and multi-omics integration Deep learning for regulatory genomics Single-cell and spatial transcriptomics Large-scale data engineering Training is highly
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Qualifications: Experience in one or more of the following areas is highly desirable: Wavefront shaping and spatial light modulator systems Multimode fiber optics Mesoscopic physics and statistical optics
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analyses and developing habitat maps using marine datasets. Applicants should possess strong analytical skills and experience with spatial modelling and statistical software such as R, Python, or MATLAB
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, spatial and hydrologic modeling, statistical analysis, high-impact technical publishing, and collaborative proposal development. In support of NRRI’s mission to deliver applied science and sustainable
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, spatial statistics, machine learning approaches, large ecological datasets Previous experience with passive acoustic monitoring and/or eBird data Familiarity with ecology and/or ornithology Demonstrated
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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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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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, statistics, and ornithology. The postdoctoral associate will be advised by Dr. Laurel Symes ([email protected] ), and will also have the opportunity to work closely with colleagues from other programs
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 13 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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-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