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Field
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sensing provides large-scale and consistent observations, in-situ data collection remains a vital component for ground-truthing, model calibration, and validation of automated monitoring. However
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; or 5) single-cell RNA/ATAC sequencing analysis and spatial transcriptomics. Candidates must hold a PhD degree. To apply, please visit: https://recruit.apo.ucla.edu/JPF10108 The University of California
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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
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datasets. Your focus will be on implementing and training generative models to decompose cylindrical projections. You will solve and refine the structures from the resulting decomposed data. You will map
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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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are as follows: Estimate the onshore technical and economic potential for CCUS in rural areas in Germany, the Netherlands and Norway. Gather high resolution spatial explicit data on (potential) CO2 sinks
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understanding of myocardial regeneration, neoangiogenesis, immunomodulation, and anti-fibrosis at the molecular level, with spatial resolution. To be successful in this role, you will hold a relevant PhD/Dphil
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digital twins to develop innovative solutions for monitoring, analyzing, and optimizing urban systems in real time. The candidate will contribute to modeling interactions between physical and digital
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] that process information in temporal rather than spatial modes to reduce their footprint. The project involves a collaboration between DTU Electro (Senior Researcher Mikkel Heuck) and Harvard University (Dr
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lead experimental efforts using advanced nanoscale optical and scanning probe techniques—including spatially and temporally resolved photoluminescence, electroluminescence, and a strong focus on