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Field
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study examining common elements in decisions across different contexts (risk, uncertainty, time; gains, losses, and mixed domain choices). Applying Bayesian techniques to develop stochastic models
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of the research project “Unreal engines — Understanding language models through resource-optimal analysis: Implicit Bayesian pragmatic reasoning & emergent causal world models”. The project uses
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opportunities for collaboration with Michigan State University, and IU’s network in cognitive modeling, AI, and human–AI decision research. This postdoctoral appointment is full-time and on-campus. Job Duties 80
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areas Biomedical applications, social determinants of health or other demographic health areas Spatial microsimulation, spatially weighted regression, combinatorial optimization or Bayesian network
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related to Riemann-Steltjes optimal control to combine PMP with Bayesian Optimisation, allowing for data-efficient learning. You will then implement and validate the new method on simulated fermentations
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resonators) and quantum (NV diamond) sensor networks for thermodynamic metrology (temperature, pressure and humidity). key words Machine Learning; Bayesian optimization; Self-correcting; Quantum Sensors; NV
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in English Candidates without a master’s degree have until 01.09.2026 to complete the final exam. Desired qualifications: Solid foundation in Bayesian statistics, empirical Bayes methods and advanced
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computing (HPC) and parallel processing to enable the analysis of massive datasets. Experience in advanced statistical inference (e.g., Bayesian statistics, spectral methods) for extracting robust patterns
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systems, neuroscience, and safety and security. The Division of Systems and Control enjoys a wide network of strong international collaborators all around the world, for example at the University of Oxford
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of data, especially heterogenous data made of several data types (continuous, texts, images, times series, networks, …). For example, social and communication networks allow users to interact through text