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statistical models (Bayesian approaches, geographical analyses) adapted to environmental data. • Carry out statistical analyses and the spatial distribution of risk between residential environmental exposures
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Researcher will work in Professor Benjamin Peherstorfer’s group (https://cims.nyu.edu/~pehersto/ ) on scientific machine learning at the Courant Institute of Mathematical Sciences where they will help
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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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to high-dimensional statistics; Bayesian statistics; resampling techniques; digital twins; uncertainty quantification; foundations of machine learning and artificial intelligence; optimization theory and
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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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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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for scientific and personal development through courses, workshops, mentoring, and collaborations. Where to apply Website https://www.academictransfer.com/en/jobs/362833/postdoc_vici_fusi/apply/ Requirements
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Is the Job related to staff position within a Research Infrastructure? No Offer Description 2-YEAR POSTDOCTORAL POSITION AVAILABLE AT NEUROSPIN/INM (PARIS, FRANCE) https://computationalbrainteam.com/en
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of neural networks, information-theoretic and optimal-transport perspectives on representation and generalisation, probabilistic numerics and Bayesian deep learning, and emerging frameworks for scientific