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Field
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learning, deep learning, and large language models (LLMs), for the analysis of high-throughput multi-omics datasets (especially single-cell and spatial omics) and large textual corpora (e.g., scientific
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of metabolic states in retinal ganglion cells; spatial transcriptomic and correlated metabolic analysis of retinal ganglion cells; treatment of retinal ganglion cells in models of degeneration; data collection
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Qualifications MINIMUM QUALIFICATIONS: PhD (or equivalent) in biology, bioengineering, computer science, physics, or a related field Strong scientific curiosity, motivation, and rigor Strong communication
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microenvironment. The project will employ genetically engineered mouse and human glioma models, along with advanced imaging techniques, single-cell and spatial transcriptomics, and molecular biology approaches
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
occurred during the October 2024 CCAMLR meeting: the expiration of Conservation Measure (CM) 51-07, which previously mandated that the maximum annual allowable catch of 620.000 t be spatially distributed
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Two fully-funded postdoctoral or PhD student positions in experimental mesoscale bioinspired materials, DNA nanoscience, and/or soft matter physics The university: Johannes Gutenberg University
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statistical analysis and computer programming in any of the following areas are highly valued: structural equation modeling, mixed effects modeling, mediation analysis, spatial modeling, web-based mapping
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Proficiency: Proficiency in Geographic Information Systems (GIS) to map and analyze spatial determinants of urban health. Predictive Modeling Skills: Ability to develop predictive models and simulation tools
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including (but not limited to) the qualifications of the selected candidate, budget availability, and internal equity. Pay Range: $74,128 - $75,611 Postdoctoral Scholarship - Cancer Biologist in Tumor Spatial
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. Contribute to the supervision of master and PhD students. Qualifications: Ph.D. in Earth Sciences, Remote Sensing, Physics, Applied mathematics, or related field. Strong background in land surface modeling