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Field
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-experiments for research purposes, Knowledge of online experiment, task and/or survey platforms (e.g. Gorilla, Prolific, etc.), Awareness of time-series, multilevel, Bayesian, or causal inference analysis
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 2 months ago
. 5. Y. Ban, X. Alameda-Pineda, L. Girin, and R. Horaud, "Variational Bayesian inference for audio-visual tracking of multiple speakers," IEEE TPAMI, 2019. 6. X. Alameda-Pineda et al., "Socially
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that generates explanatory theories with a question-answering inference machine, and operating with explicit notions of uncertainty so as to mitigate overconfident predictions [1]. A complementary line
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of: Developing model visualisation methods to enable interactive and dynamic model building. Robust selection and estimation in regression type models. Variable selection and inference for statistically
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groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative projects with other group members and our
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equation modeling, survival analysis and Bayesian inference Oversee the management and sharing of datasets for the CNDS including large consortium datasets across 2 different 4-site projects. Oversee data
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theoretically, in tight collaboration with experimental groups. The theoretical methods include stochastic modelling, MD simulation, and Bayesian inference; the position will also include joint collaborative
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networks, Bayesian inference, computational neuroscience, mathematics.
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that leverage state-of-the-art AI methods (deep learning, generative AI, Bayesian modelling, active learning, etc.) to combine cellular imaging data, chemical compound structure, viral genomes and other omics
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applications of Bayesian inference approaches is highly desirable • Expert knowledge in the areas of social and computational neuroscience • You should be a team player with high social and excellent