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. The BayesCompare project is a FNR funded project on Bayesian comparisons between artificial and natural representations to improve our understanding how natural and artificial intelligences process information
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these relate to societal and individual-level challenges. The BayesCompare project is a FNR funded project on Bayesian comparisons between artificial and natural representations to improve our understanding how
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project on Bayesian comparisons between artificial and natural representations to improve our understanding how natural and artificial intelligences process information. The project is led by Heiko Schütt
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. Experience leading investigations linking simulations to observational data. Experience with statistical characterization of data, preferably within a Bayesian framework. Job Description: A Post-doctoral
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methodologies. Understanding of integrating Bayesian approaches in NN-based model Knowledge of model deployments to cloud platforms or past work with AutoML tools. Knowledge of MLFlow for maintaining model
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clinical trials in patients with cancer; to identify and validate predictive biomarkers of clinical outcomes in cancer; and perform meta- analyses using the Bayesian framework. The projects will lead to both
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on large-scale analysis of complex traits, including Bayesian machine learning and linear mixed model approaches for trait prediction and association in high-dimensional genomic datasets, as well as methods
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work on large-scale analysis of complex traits, including Bayesian machine learning and linear mixed model approaches for trait prediction and association in high-dimensional genomic datasets, as
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on the development of Bayesian statistical/machine learning methods for the data integration analysis of high-throughput imaging and molecular data (i.e., genome, transcriptome, epigenome, and more). The methods would
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at the intersection of systems neuroscience and computational modeling. Our lab is broadly interested in Bayesian inference, perception, multisensory integration, spatial navigation, sensorimotor loops, embodied