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Field
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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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The Faculty of Spatial Sciences is looking to appoint a postdoctoral researcher on the topic of regional innovation systems. The main responsibility will be to initiate and perform research
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diversity and dynamics of metabolic states in retinal ganglion cells; spatial transcriptomic and correlated metabolic analysis of retinal ganglion cells; treatment of retinal ganglion cells in models
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the research group of Professor Klaus Nordhausen in the project “Signal recovery in noisy spatial data”. The research group develops modern and efficient multivariate statistical methods tailored
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proteome in heart-specific cell lines and primary tissue. It will utilize disease model systems to characterize unique cell surface signatures for cardiomyocytes, coronary endothelial cells, and fibroblasts
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hydro-climate studies. Strong background with GIS tools and spatial analysis techniques. Demonstrated expertise in climate variability assessment and the use of climate models. Experience with
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proteome in heart-specific cell lines and primary tissue. It will utilize disease model systems to characterize unique cell surface signatures for cardiomyocytes, coronary endothelial cells, and fibroblasts
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developing biotechnological solutions to address challenges in renewable energy, sustainable manufacturing, and human health. Our group specializes in dynamical and spatial control of engineered metabolisms
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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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researcher position with an anticipated duration of 16 months, to work under the direction of Dr. Melissa Lucash. In our lab, we use a variety of tools (e.g. big data, spatially explicit simulation modeling