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providing a basis for decision support and lifetime extension. This may be obtained by comparing existing design practice with results based on application of Bayesian updating to account for uncertainties in
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expression and developability. Propose and validate optimization tools for performing (Bayesian) design of experiments. System validation and iterative refinement based on empirical data. Test and refine
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systems , Quantum Transport in topological phases , Radiation Therapy Simulation , RF Engineering , Scattering amplitudes , simulation-based inference , single- and multicomponent quantum hydrodynamics
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). The goals are to develop new computational methods that allow the scientific inference of explainable attributes to describe human behavior and self-reports as well as to make progress in the computational
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ethnomycology or ethnobiology large-scale (ethnographic) database construction phylogenetic comparative analyses with Bayesian computational tools The applicant must have the ability to work independently and in
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will be developed using the OpenFOAM toolkit. A modelling workflow will be created, and then used as the basis for the optimisation, potentially using tools such as Bayesian Optimisation. In addition
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, perform cutting-edge analytical techniques for causal inference and prediction, and writing papers for both an academic audience and for practitioners (managers and/or policymakers). Desired Qualifications
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to reason about software (e.g., LLM agents for finding and fixing bugs) Static and dynamic program analysis (e.g., to infer specifications) Test input generation (e.g., to compare the behavior of old and new
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enable the model to infer health-related information directly from NMR spectra of human blood. To this end, the model will be pre-trained using self-supervised learning on large-scale, partly synthetic
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methods, including modern machine learning methods, to draw inferences from register data. A third project “Integrative machine and deep learning models for predictive analysis in complex disease areas“ is