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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 2 months ago
-driven sampling within hard-to-learn areas for simulation-based neural network training, NeurIPS ML4Phys 2023: https://hal.science/hal-04305233v1 Melissa: Simulation-Based Parallel Training, NeurIPS AI4S
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University of California, San Francisco | San Francisco, California | United States | about 1 month ago
to execute data analyses. Current Major Projects Rapid Research in Diagnostics Development for TB Network (R2D2 TB Network) – This NIH U01-funded project has established a platform for identifying promising
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approaches; network design and analysis; and other related topics in optimization, modeling, and decision sciences. 2. Statistics: Candidates interested in this position must have solid foundations in
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courses within the research methodology (Data Collection) and statistics modules (Mixed Models, Bayesian Approaches, Network Models, etc.). Additionally, the candidate may also contribute to teaching across
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such as imaging, spatial, network, and genomics data. The appointment is expected to begin on August 15, 2026. Review of applicants will begin on November 17, 2025, but the position will remain open until
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theories from tractable models (probabilistic circuits) and Bayesian statistics to tackle the reliability of machine learning models, touching topics such as uncertainty quantification in large-scale models
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with modeling, time-series analysis, or network analysis. Oberlin is situated on the outskirts of Cleveland, combining a cozy small-town atmosphere with the cultural amenities of a major city. The
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. There will also be common meetings with the other 14 PhD students in the doctoral network, including 3 training schools. As a participant of the project, the PhD student will become part of a team at DTU
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Denmark and Politecnico Di Torino, Italy. There will also be common meetings with the other 14 PhD students in the doctoral network, including 3 training schools. As a participant of the project, the PhD
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transportation systems modeling and simulation that could involve integrated machine learning and network equilibrium/simulation, surrogate models/ reduced order emulators or Bayesian or interpretable machine