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Department of Spatial Economics The Econometrics and Data Science department aims at pushing the academic frontier in methodology development for quantitative, statistical modeling of data, ranging
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the Environmental Geography department in collaboration with the Environmental Economics department. The Environmental Geography department conducts interdisciplinary research on the spatial aspects of environmental
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programming skills (Python; familiarity with deep learning frameworks such as PyTorch or TensorFlow is an advantage); Affinity with probabilistic modelling and spatial data analysis; Interest in the physical
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program’s horizon. You will acquire project funding, and contribute to outreach, mentor PhD students and postdocs, and work with a large network of scientists. This is your chance to innovate and shape a
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researchers, PhD students and postdocs, as well as MSc and BSc students. In addition, our museum and our network of ministries, companies, and educational institutions offer advantages for your outreach
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the extraction of critical minerals. Across these settings, the project interrogates how violence and resistance emerge through different spatial, temporal, and stratigraphic scales, and how these processes can be
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developments, you will work closely with the other PhD, postdocs, engineers in the lab, and other collaborators from TUM and ETH, to establish a digital twin for construction, and optimize CAML hardware
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spatial scales into a crop modelling framework and predicting daily targets for photosynthesis and transpiration rates (all developed by other researchers in the project consortium). Based on these targets
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such changes contribute to long-term treatment success. A collaborating postdoc will perform advanced MRI brain imaging in a subset of participants to investigate changes in the olfactory bulb and connected
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Advisory Committee and National Science Program Council. Our team consists of professors, scientists, technicians, office staff, postdocs, PhD students and undergraduate students. This ensures a diverse and