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modelling. MISSION You will actively contribute to the development and evaluation of new hybrid computational method to predict biological tissue deformation with subject-specific material properties
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future quantum simulations at the intersection of subatomic physics and quantum information science. The successful candidate will also lead peer-reviewed publications and develop computational methods
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Materialist theories Developing appropriate (design) research methods Project management About the project:Thinking with Things is funded by the Austrian Science Fund (FWF) and will start on January 1, 2026. It
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Foundation. The position will suit researchers interested in developing state-of-the-art methods in economics to develop our understanding of current and future environmental impacts of artificial intelligence
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National Aeronautics and Space Administration (NASA) | Greenbelt, Maryland | United States | about 12 hours ago
operators for fire observations for atmospheric data assimilation Implement ensemble methods in the fire emissions estimation and estimate uncertainties Utilize bi-phasic FRP retrievals for dynamic
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simulations on the Aurora supercomputer, using AMReX (https://amrex-codes.github.io/amrex/ ) and the lattice Boltzmann method (LBM). The candidate will develop flow/geometry-aware refinement strategies that go
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an interest in how psychological theory can improve synthetic data and in deepening our understanding of when and why LLM-generated responses approximate human behavior. The project involves a collaboration
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forecasting. Familiarity with ensemble methods, Bayesian approaches, and uncertainty estimation. Experience with large-scale or messy real-world data (structured and/or unstructured). Interest in or experience
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proteins in non-bilaterian animals (sponges, placozoans, cnidarians, ctenophores). The ideal candidate will have a background in biochemistry, cell biology, or evo-devo, and experience applying these methods
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of neurodegeneration. Practical experience with C90rf72 genetic models in Drosophila. Preferred Qualifications: Use of Gal4 and Gal80 methods in Drosophila. Q-RT-PCR. Brief Description of Duties: | The Postdoctoral