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Bayesian Index Tracking: optimisation by sampling School of Mathematical and Physical Sciences PhD Research Project Self Funded Dr Kostas Triantafyllopoulos, Dr Dimitrios Roxanas Application
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Intensive Care National Audit & Research Centre - ICNARC; | London, England | United Kingdom | 16 days ago
Clinical Trials Unit (CTU) that is designing and delivering cutting-edge clinical trials employing frequentist and Bayesian methods in adaptive and platform trial designs. We are looking for a Principal
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related to staff position within a Research Infrastructure? No Offer Description Support in research on Bayesian optimization methods. Data analysis and modeling. Development of prototypes and software
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Bayesian machine learning for robotics applications in industrial manufacturing and medical diagnosis, SDU Robotics invites applications for one or more fully funded Research Assistant positions
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with researchers at Chalmers and the University of Gothenburg. You will explore how Bayesian methods can enable risk-aware, real-time trajectory planning and contribute to the development of autonomous
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University of Gothenburg. You will explore how Bayesian methods can enable risk-aware, real-time trajectory planning and contribute to the development of autonomous vehicles that are both safe and trustworthy
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: Cuantificación de Incertidumbre Bayesiana (Bayesian Uncertainty Quantification, BUQ) Appl Deadline: 2025/10/30 11:59PM * (posted 2025/09/08, listed until 2025/10/30) Position Description: Apply Position
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Location: South Kensington Campus About the role: We are looking for a motivated Research Associate in Bayesian Optimisation & Experimental Design to work with Professor Ruth Misener and Dr Calvin
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learning by using Bayesian learning principles. Among other things, Bayesian learning gives AI systems the ability to quantitatively express a degree of belief about a prediction or statement. By bridging
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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