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processes. A demonstrated interest in data visualization and large-scale data analysis is highly desirable. The ideal candidate will have a keen interest in understanding complex biological systems
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activities aimed at developing and using biomarker analysis in blood samples for next generation cancer diagnostics. The work will also include studies in basic tumor biology, where we use various in vitro
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and Data Science for Spatial Genomics in Diabetes This position centers on the development and application of machine learning, image analysis, and integrative omics approaches to spatial
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. Importance will also be placed on experience of qualitative methods for data collection and analysis. Given the character of the research project importance will also be placed on good knowledge of both
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motor behavior analysis. Technical experience with imaging, molecular biology, immunohistochemistry, in situ hybridization are also highly valued. Technical experience with embryo electroporation and /or
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contacts with other disciplines nearby and interacts with biomedicine, pharmacy, physics and materials science. Scientists with expertise in biophysical methods of interaction analysis are responsible for a
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microorganisms, and developing of spectral collection and analysis protocols that will allow this biochemical data to be effectively used to support optical microscopy-based deep-learning algorithms for species
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test planning, instrumentation (e.g., strain gauges, LVDTs, DIC), execution of large-scale tests, and data analysis. Solid understanding of structural behavior, failure mechanisms, and durability issues
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biomass characterization, biomaterial characterization and application. Experience in glycomic analysis is highly recommended. Laboratory experience in biomass transformation in materials and water based
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-unique CO2 experiments, cutting-edge NMR spectroscopy and isotopomer analysis (doi: 10.1111/nph.20358). Two postdocs will work together to conduct plant ecophysiology experiments, and to analyze samples by