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Field
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, simulations, and games, which use a variety of AI technologies to learn from, collaborate with, support, or improve humans; Deep Learning for Perception: Use of deep learning algorithms for computer vision
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migration Developing appropriate statistical algorithms for updating model parameters estimates Working with database manager to organize the fish data and environmental covariates Analyzing data and
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for differentiating effectful programs such as gradient estimation of probabilistic programs, implicit function differentiation, compositional Bayesian inference techniques); analyzing what is required (e.g., choice
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has a strong background in control engineering, with documented expertise in optimal control, adaptive control and online optimization, stochastic systems, Bayesian inference, and state estimation and
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Inria, the French national research institute for the digital sciences | Saint Martin, Midi Pyrenees | France | 20 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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designs such as observational study, randomized clinical trial, adaptive randomizations, Bayesian analysis of randomized trials, conventional meta-analysis, meta-regression, and network meta-analysis Work
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randomizations, Bayesian analysis of randomized trials, conventional meta-analysis, meta-regression, and network meta-analysis. · Develop as an educator by taking an active teaching role in POCUS and EBM
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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