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Inria, the French national research institute for the digital sciences | Talence, Aquitaine | France | 12 days ago
site in the PACA region of France. They consist of a mirrored side and a painted side. Rather than resorting to manual computer graphics work, the general aim of the project is to to develop the lightest
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Job Description Job Responsibilities: -Develop method for target and non-target analysis of emerging contaminants in different matrixes. -Adapt advanced materials and technologies for emerging
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Center is seeking a Postdoctoral Researcher to work on ion trap quantum computer and quantum network projects, supporting/advancing research in quantum information science. The position involves designing
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responses approximate human behavior. The project involves a collaboration between behavioral and computer scientists. The ideal candidate has some knowledge in both areas, and the specific behavioral domain
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-depth expertise in Computer Vision and Photogrammetry. - Mastery of state-of-the-art Neural Rendering (NeRF, NeuS, SDF). - Knowledge of Photometric Stereo methods. Operational Skills: - Advanced
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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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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