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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 21 days ago
are available, from computer graphics, computer engineering, computational physics, biology and chemistry, and so on. When training data is produced from simulation codes, it can be generated along with
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principles and analytic methods relevant in health services research Advanced knowledge of statistical computing and/or Bayesian inference Advanced programming skills in a common statistical software package
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AUSTRALIAN NATIONAL UNIVERSITY (ANU) | Canberra, Australian Capital Territory | Australia | 2 months ago
deep learning theory and practice. Applicants with expertise in probabilistic modelling, approximate inference, deep learning, or Bayesian optimisation are encouraged to apply. Interpretable Machine
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descent, random forests, etc.) and deep neural network architectures (ResNet and Transformers). Preferred Qualifications: Knowledge of Approximate, Local, Rényi, Bayesian differential privacy, and other
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 30 days ago
00061514 Vacancy ID P020571 Full-time/Part-time Permanent/Time-Limited Full-Time Permanent If time-limited, estimated duration of appointment Hours per week 40 Work Schedule Monday – Friday, 8:00 am – 5:00
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 23 days ago
00061514 Vacancy ID P020571 Full-time/Part-time Permanent/Time-Limited Full-Time Permanent If time-limited, estimated duration of appointment Hours per week 40 Work Schedule Monday – Friday, 8:00 am – 5:00
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vaccination barriers and facilitators, develop forecasts of vaccine coverage for existing and novel vaccines (e.g. HPV, RSV, malaria), and support the design and implementation of small area estimation and
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features to behavior using GLMMs/Bayesian models; conduct sensitivity and robustness checks. * Method validation: benchmark alternative pipelines (filters, burst detectors, forward/inverse models); perform
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-armed Bandits, Bayesian Optimization. Automated Model Design and Tuning: Neural Architecture Search, Hyperparameter Optimization. Computer Networking: Resource-Constrained Networking (e.g., Internet
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Centre (NCN). The Principal Investigator is Dr. Eng. Piotr Kopka, email: Piotr.Kopka@ncbj.gov.pl Project description: The project aims to develop a new class of inverse Bayesian models called STE-EU-SCALE