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modeling and analysis. Ability to select, implement, diagnose, and adapt parameter-estimation or statistical-inference methods to suit the model, data structure, and scientific question. Experience with
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qualifications Publications at top machine learning or computer vision conferences (NeurIPS, ICML, ICLR, CVPR, AISTATS etc.) are highly meriting. Expertise in Bayesian methods, generative models, multimodal models
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of avian biodiversity information worldwide. Jointly, these approaches can provide complementary geographic and temporal coverage, and integrating them can improve estimates of species occurrence, phenology
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areas : 1/ Development of methods to estimate residential environmental exposures • Develop spatialized indicators of exposure to atmospheric contaminants (gaseous pollutants and pesticides) based
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than 18,500 people, including over 14,000 students and 4,000 researchers from more than 120 different countries. Postdoctoral Researcher in Multimodal Human Sensing and Advanced Behavioral Data Analysis Mission
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. Experience with uncertainty quantification, Bayesian inference, inverse modelling, parameter estimation, or model calibration. Experience with high-performance computing, surrogate modelling, reduced-order
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. This large multimodal dataset allows us to estimate and test different computational models of the decision and learning processes. One postdoc is currently working on the MEG and iEEG data, and one PhD
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the theory of brain-inspired algorithms and apply them to complex, real-world problems. The successful candidate will join an interdisciplinary team of computer scientists, mathematicians, engineers, and
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thereafter. The position will be available for a two-year period, with possibility of extension. You will be part of a research environment focusing on estimating greenhouse gas (GHG) emissions, reactive