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Field
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. Strong interest in gene regulation dynamics, cancer research, and translation medicine Experience in computational analysis of biological data Experience with single-cell, transcriptomics, spatial biology
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 7 days ago
extrapolate LiDAR-constrained structural data across broader spatial and temporal scales. The participant will collaborate with researchers to evaluate encoder adaptations that incorporate both synthetic
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recognized leader in cartographic design, dynamic mapping, mobile application development, spatial data analysis, visualization, and GIS. The Lab conducts interdisciplinary collaborative projects with research
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 20 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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analysis of single cell RNA-sequencing and spatial transcriptomic datasets. Mentor undergraduates, research technicians, and rotating graduate students. Collaborate with researchers inside and outside
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with computational analysis of spatial transcriptomics or other high-dimensional datasets and strong data management skills are highly desirable. We are seeking an independent and collaborative scientist
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Website https://seuelectronica.urv.cat/treballar-a-la-urv/pi26031english.htm Requirements Research FieldChemistryEducation LevelPhD or equivalent Skills/Qualifications PhD in Chemistry, Nanoscience
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disease. Apply and optimize advanced spatial biology techniques, such as spatial transcriptomics, proteomics, and multiplexed imaging, to analyze brain tissue. Lead data analysis and interpretation
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through the analysis of oceanographic samples, interpretation and synthesis of multidisciplinary datasets, dissemination of research findings through publications and presentations, and archiving of data in
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, electrical polarisation and, then evaluate cell-matrix interactions using live-cell imaging, molecular assays and, spatial transcriptomic approaches to identify key mechanisms linking matrix mechanics