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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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biostatistical training and skills, including longitudinal and correlated data; familiarity with advanced analytics including machine learning, Bayesian methods, and causal inference also desired. Strong written
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for optimisation. (3) Machine Learning-based optimisation: implementation of a preliminary optimisation pipeline (e.g., Bayesian optimisation or reinforcement learning) integrated with the simulator to test
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | about 1 month ago
Bayesian statistics, AI-assisted inverse problems, planetary remote sensing, and environmental monitoring. Where to apply Website https://jobs.inria.fr/public/classic/en/offres/2026-09787 Requirements Skills
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, candidates are required to complete a scientific programming task in the subject area of the advertised position: https://www.hpc.uni-wuppertal.de/de/peter-zaspel/challenge-in-bayesian-inference-for-climate
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Discrete Mathematics Probability and Statistics Regression Analysis Time Series Analysis Bayesian Statistics Mathematical Foundations of Machine Learning Contribute to curriculum development and course
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equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https
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-country survey datasets for comparative analysis. Conceptualize and refine a theoretical framework integrating intersectionality and stigma processes. Develop and code a Bayesian meta-regression to pool and
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, methodologies, and information derived from Bayesian modeling, data science, cognitive science, and risk analysis. Its primary objective is to create advanced forecasting models, generate meaningful indicators
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specimens to estimate historical age structures over the last 150 years. Forecasting Shifts in the Pollination Service Window. The researcher will use Bayesian inference (e.g., Integrated Nested Laplace