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schools in the world. For more details, please view https://www.ntu.edu.sg/mae/research . We are looking for a Research Associate / Research Engineer II to conduct cutting-edge research and software
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Postdoctoral Research Assistant in Decision-making under uncertainty for robots Grade 7 : £39,424 - £47,779 per annum We are looking for a post-doctoral research assistant to join the GOALS group
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emissions and exposures from observational data. -Work may include statistical or Bayesian inverse modeling, data assimilation, optimization, uncertainty quantification, numerical methods, and related
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description What uncertainty in clinical evidence is acceptable for regulatory
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Environmental Engineering (CEE). For more information, please visit: https://earthobservatory.sg , https://ntu.edu.sg/ase , and https://ntu.edu.sg/cee . We are looking to fill a total of 5 Research Fellow
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 20 hours ago
, but are not limited to, robust and stochastic optimization, generative and foundation models, reliable and robust machine learning, uncertainty quantification, sequential decision-making, and AI systems
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of statistical and probabilistic methods for the analysis of complex data and systems. Research topics include distributional modelling, stochastic dependence, extreme-value phenomena, uncertainty quantification
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. Jochen Peter ([email protected] ) or dr. Toni van der Meer ([email protected] ) Where to apply Website https://www.academictransfer.com/en/jobs/364079/phd-candidate-agents-of-doubt-a… Requirements
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Inria, the French national research institute for the digital sciences | Rennes, Bretagne | France | about 22 hours ago
a growing interest in geophysical sciences and climate studies in developing flow models that incorporate noise to account for modelling uncertainties or errors. The introduction of noise into ocean
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structure and fisheries data. Understanding how these assumptions affect model performance and management advice is critical for identifying key sources of uncertainty and determining where methodological