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Your Job: This PhD project develops a Bayesian inference framework for hybrid model- and data-driven modeling of metabolism, with a particular focus on handling model misspecification. By combining
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at the interface of computational systems biology and mathematics/statistics with a strong attitude to open research software development. For more information visit http://www.fz-juelich.de/ibg/ibg-1/modsim
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Student or Postdoc (f/m/d) for the project Theory and Algorithms for Structure Determination from Single Molecule X‑Ray Scattering Images Project description Single molecule X‑ray scattering experiments
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, please visit: https://qbm.genzentrum.lmu.de/application/ Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content
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, contribute to a better world. We look forward to receiving your application! We invite applications for a fully funded PhD student position to join the research group of Jan Glaubitz to work on Bayesian
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, including Tikhonov regularization [3], Bayesian approaches [4], and compressive sensing or sparse regularization methods [5]. However, with the emergence of Physics-Informed Neural Networks (PINNs), new
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or dynamic environments. At the same time, radio sensing and semantic mapping provide access to rich signal-level information that implicitly contains predictive structure. Certain radio features, although not
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highly advantageous: Scientific programming in Python or MATLAB Probabilistic methods, Bayesian inference, or stochastic modelling Structural mechanics, material modelling, or multi-physics simulation Data
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and ML driven screening and optimization workflow to improve the generality of modern synthetic methods. Our first objective is to identify structural patterns and scaffolds that are accessible by
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. - Bibliographic research - Analysis of capture-mark-recapture data, fecundity data, population structure and size data, and hunting bag data - Development and adjustment of integrated population models