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Field
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Gaussian processes with learning capabilities is essential, including data association and other Bayesian methods. You will join a collaborative research environment at the University of Sheffield, working
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interdisciplinary collaboration. Faculty and students conduct innovative research in Bayesian methods, causal inference, data science, machine learning, statistical genetics, longitudinal and survival analysis, and
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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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, computer/data science or relevant topics in other fields. Doctoral dissertation must be submitted for evaluation by the closing date. Only applicants with an approved doctoral thesis and public defence are
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opportunity not to be missed. Cambridge Judge Business School is seeking a talented and motivated Research Associate to join the El-Erian Institute for Behavioural Economics and Public Policy. Situated
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modeling, sensitivity and robustness analysis, Bayesian inference, inverse problems, parameter estimation, or model validation. Experience or strong interest in scientific AI/ML, including surrogate or multi
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, ● Methods for heterogeneous treatment effects estimation, ● Methods for multiple exposures, multiple outcomes, ● ML and AI methods for causal inference, ● Bayesian causal inference, ● methods
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Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial | Portugal | 2 months ago
15 Jul 2026 Job Information Organisation/Company Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial Department Human Resources Research Field Engineering » Computer
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confidence estimation pipelines for LLM-generated causal claims [4, 5], so that the world model's outputs come with conformal-style probabilistic bounds that can be plugged directly into Bayesian-oracle-style
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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