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GIS-Based Model for Active Citizenry Street-Level Environment Recognition On Moving Resource-Constrained Devices Bayesian Generative AI (PhD Project) Explainability and Compact representation of K-MDPs
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wild and domestic animal populations wildlife diseases and conservation network analysis of disease spread phylodynamics model-based statistical inference using Bayesian approaches vector biology
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Bayesian inference, stochastic algorithms and simulation-based inference; and statistical machine learning. OCBE has collaborations with leading biomedical research groups in Norway and internationally. OCBE
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guiding materials measurement experiments to acclerate learning the synthesis-process-structure-property relationship. Machine learning methods include, but are not limited to, Bayesian inference
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are required. Advanced competence in multiple approaches, such as neural ODEs, LLMs, bayesian, Lasso, large language models, and ensembling methods is required Experimental Immunologist Research Scientist
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, including sequential Monte Carlo methods, Gaussian processes and Bayesian compressed sensing. Applicants from different backgrounds are encouraged to apply depending on the specific nature of the project
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This PhD project is funded by a successful ARC Discovery Project grant: "Improving human reasoning with causal Bayesian networks: a user-centric, multimodal, interactive approach" and the successful
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Sequential Monte Carlo Methods for Bayesian Inference in Complex Systems School of Electrical and Electronic Engineering PhD Research Project Self Funded Prof Lyudmila Mihaylova Application Deadline
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machine learning, Large Language Models, Stochastic optimization, Transfer & Evolutionary optimization, Bayesian optimization or Complex Design Optimization. Key Responsibilities: Support and conduct
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characterization tools for closed loop experiment design, execution, and analysis, where experiment design is guided by active learning, Bayesian optimization, and similar methods. A key challenge is the integration