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Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig | Leipzig, Sachsen | Germany | 3 months ago
across domains. Under this umbrella, we explore. Spatial navigation, temporal, episodic, and working memory Learning, decision making, and knowledge acquisition Translational research on population coding
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National Aeronautics and Space Administration (NASA) | Pasadena, California | United States | 21 days ago
, with the capability to measure air pollutant and carbon cycle-relevant gases at good spatial resolution and now (with GEO satellites) better temporal resolution than has historically been possible from
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power. The work involves quantifying conflicts and synergies between different sustainability goals in the forest landscape using simulation and optimisation. The analysis will be based on spatially
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policy and/or land policy Strong academic writing skills and a clear track record or potential to publish in leading journals Experience with qualitative research (policy analysis, interviews, comparative
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areas Biomedical applications, social determinants of health or other demographic health areas Spatial microsimulation, spatially weighted regression, combinatorial optimization or Bayesian network
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. Experience with Bayesian methods, graph/network analytics, reinforcement learning, or other advanced AI approaches relevant to industrial systems. Experience with geospatial analysis, spatial data integration
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complex ocean environments over a range of spatial scales and frequencies. 20% Develop computationally efficient approaches for propagation modeling that allow their execution on embedded systems in
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secured funding support for ~2 years. The goal of this project is to design and develop spatially explicit decision support tools and assist with updating an Implementation Plan to identify and prioritize
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-environment-climate public goods (AECPG). By combining insights from results-based, collective and spatially targeted schemes with novel financing and robust monitoring, REWARD seeks to build scalable models
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National Energy Technology Laboratory (NETL) | Pittsburgh, Pennsylvania | United States | about 6 hours ago
, increased storage) Apply geostatistical methods (e.g., kriging) to characterize the spatial heterogeneity of key reservoir parameters (e.g., porosity, permeability) and quantify subsurface uncertainty through