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Bayesian inference, likelihood-free inference, uncertainty quantification, identifiability analysis, or scientific machine learning. Strong programming skills (Python, Julia, Matlab, C++, or similar). Strong
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quantum coupling between atoms and cavity to observe superradiance with an ytterbium gas. The next experimental objective is to transport ytterbium atoms to the cavity via an optical conveyor belt. In
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 hours ago
and Bayesian methods. Experience using DOE computing allocations (NERSC, OLCF, ALCF). A record of productive collaboration in multi-institutional projects. Special Physical/Mental Requirements Special
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, for a defined department program (s), often of a large and/or complex nature. Carries out established program objectives and directives. Follows established guidelines or protocols and determines
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d’Hebron Research Institute (VHIR), Vall d’Hebron University Hospital (Barcelona, Spain), DETECTIVE is looking for a Doctoral Candidate (DC) to work on Work Package 1. As DC10, your research objectives
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Professor Harri Lähdesmäki. The position offers a broad local research network in Bayesian machine learning and computational biology. Your network and team Dr Martinelli is an independent Research Fellow
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strong methodological profile, including Spatial and Spatio-Temporal Statistics, Functional Data Analysis and Process Monitoring, Bayesian Statistics, and Artificial Intelligence in Statistical Analysis
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Electron diffraction experience, including low-dose data collection and sample preparation. Experience with self-driving labs, materials acceleration platforms, active learning, or Bayesian experimental
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. Funding Opportunities: Identifying and prioritizing grant and external funding opportunities that will offer the highest yield for the lab's objectives, including making decisions on when and how to pursue
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multivariate responses. Robust, scalable, and computationally efficient stability selection methods that integrate frequentist and Bayesian strengths, with visualisation tools to assess feature stability