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, United States of America Subject Areas: Bayesian inference; inverse problems Appl Deadline: 2025/12/31 11:59PM (posted 2025/10/09, listed until 2026/04/09) Position Description: Apply Position Description The Department
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motif, hence renders the identification of the binding protein difficult. Here we propose for the first time to apply the Bayesian information-theoretic Minimum Message Length (MML) principle to optimise
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physics, Bayesian inference, and complex systems theory. You will contribute to method development, simulation and validation in close collaboration with experimental partners. Key Responsibilities: Carry
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Details Panel (longitudinal) data enables learning the dynamics and relations of (groups of) units, strengthening the inference on both cross-sectional and dynamic parameters. The dominant approach
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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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. Compare advanced deep learning–based methods with probabilistic approaches. Collaborate with researchers at Chalmers, the University of Gothenburg, and international experts in Bayesian inference and
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. Collaborate with researchers at Chalmers, the University of Gothenburg, and international experts in Bayesian inference and optimal control. Present your results at international conferences and publish in
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inference, analysis of high-dimensional and -omics data, Bayesian methods, and clinical trials, with active collaborations in cancer, aging, HIV, and the analysis of large-scale health data. The School
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and learned surrogates with clear statistical validation; Bayesian inverse problems and data assimilation via measure transport and amortized inference; robustness and distribution shift in scientific
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silico model of normal development. Bayesian inference will calibrate model parameters and highlight control points, with predictive accuracy benchmarked against existing perturbation datasets. O3. Map