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Field
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with planet formation, modelling the physico-chemical processes in disks, and to link these models to astronomical and solar system observations, and geology. Current research topics include
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multiple Jurassic cold snaps using stable carbon isotope fractionation measured in molecular fossils e.g. phytane. Integrated with Earth System models, this approach allows to quantify carbon–climate
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Research Center for Molecular Medicine (CeMM), ÖAW | Vienna, Virginia | United States | about 2 months ago
regulation of oncogenic competence and drug sensitivity. This project develops machine learning models (sequence-to-function, cell state model, etc) to predict gene regulatory and cell state changes under
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statistical modeling, including development and validation of predictive models using large-scale data. 3. Proficiency in large language model (LLM) and natural language processing methods for analysis
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urban models and computational fluid dynamics (CFD) simulations can improve the prediction of urban airflow and the effects of Urban Air Mobility (UAM) operations. Urban environments present complex
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methylation, chromatin accessibility), and clinical data. · Develop, apply, and benchmark machine learning and statistical models for subtype discovery, classification, and outcome prediction. · Contribute
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the climate-sensitive pathogen Vibrio vulnificus, source of fulminant septicemia. Our goal is to gain the knowledge to a) effectively forecast the traits of emergent virulent strains, b) predict
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are English and German. The hired person will work on the project Predicting Arctic Tundra ecosystems development (ARTECO), which is funded by the Austrian Science Fund (FWF). This is and a cooperation project
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Max Planck Institute of Animal Behavior, Radolfzell / Konstanz | Konstanz, Baden W rttemberg | Germany | 3 months ago
that opens up unique research opportunities. The goal of our basic research is to develop a quantitative and predictive understanding of the decisions and movements of animals in their natural environment
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and neural activity. In particular, Postdoctoral AI Researchers may help develop brain foundation models that predict patterns of neural activity from large-scale, multi-regional recordings. Areas