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Field
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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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from, collaborate with, support, or improve humans; Deep Learning for Perception: Use of deep learning algorithms for computer vision, image and audio processing, and models of perception. The focus is
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six months at the beginning of employment. Position description The successful candidate will work within the research project “Advances in generalized Bayesian inference via differential-geometric
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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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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
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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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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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The relationship between the information-theoretic Bayesian minimum message length (MML) principle and the notion of Solomonoff-Kolmogorov complexity from algorithmic information theory (Wallace and
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will be grounded in rigorous mathematics coupled with a sound understanding of the underlying earthworm ecology. Bayesian inference methodologies will be developed to estimate where and when behavioural
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communication and collaboration skills Preferred: Experience with simulation-based inference and Bayesian methods Familiarity with cosmological simulations or observational cosmology ML architecture design and