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between biodiversity and climate change. The postdoctoral position is embedded in the the collaborative project Past to Future: towards fully paleo-informed future climate projections (P2F; https
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how they resonate into the present (https://www.uni-kiel.de/en/cluster-roots ). ROOTS combines expertise from a wide array of disciplines ranging from archaeology to other natural sciences, life
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Max Planck Institute for Demographic Research, Rostock | Rostock, Mecklenburg Vorpommern | Germany | 2 months ago
-based data, natural experimental designs, genetically-informed social epidemiological data, advanced dynamic modelling techniques, and a combination of theoretical frameworks. Our offer We provide a
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | 15 days ago
techniques, and a combination of theoretical frameworks. We provide a stimulating research-oriented community, an excellent infrastructure, and opportunities to work with exciting datasets. The successful
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to reproducible open-source research software and data workflows Collaborate within an interdisciplinary context combining seismology, geodesy, and climate modelling Present and publish research results
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engineering, and quantitative live-cell imaging to probe and model these processes. By combining stem cell biology with cutting-edge microscopy and physical concepts, we aim to establish a predictive framework
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. The Group will combine social theories such as demographic transition, life course approach, and social determinants of health, with the emerging biological theory linking reproductive ageing to the broader
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Alfred-Wegener-Institut Helmholtz-Zentrum für Polar- und Meeresforschung | Potsdam, Brandenburg | Germany | 2 months ago
sea ice influence stratosphere–troposphere coupling and downstream extreme events, using advanced high-resolution ICON simulations and causal discovery techniques. The project will combine process-based
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kinetic mechanisms and key elementary reactions involved. Addressing this shortcoming is the goal of this project. Please visit the DFG research unit description for more information on the topic https
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propose to combine machine learning techniques with formal methods. We will focus on safe reinforcement learning of motion planning problems for autonomous vessels. Motion planning is particularly