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Field
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Bayesian ML approaches for path inference; introducing sensors; behaviour classification; resource-constrained active-learning; other IoT applications; microbattery development and field experiments and
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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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Helmholtz-Zentrum Dresden-Rossendorf - HZDR - Helmholtz Association | Gorlitz, Sachsen | Germany | 26 days ago
field # Knowledge of dynamical systems and network theory # Previous knowledge of pattern formation theory and of Bayesian inference methods is a plus # Previous programming experience in Python is
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, hydro-acoustics, data science, geodynamics, geophysics, statistics, Bayesian inference ⁃ Experience with statistical analyses and machine learning techniques ⁃ Programming in C / python / Julia
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for differentiating effectful programs such as gradient estimation of probabilistic programs, implicit function differentiation, compositional Bayesian inference techniques); analyzing what is required (e.g., choice
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project developing Bayesian causal inference methods for mediation analysis using Electronic Health Records (EHR) data. The Research Fellow will design and implement Bayesian methods and software
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programming language Experience with statistical inference or machine learning methods (e.g. ABC, Bayesian modelling) A proven publication record with at least one first author publication in a peer-reviewed
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six months at the beginning of employment. Position description The successful candidate will work within the research project “Advances in generalized Bayesian inference via differential-geometric
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probability, partial differential equations, and mathematical physics. In statistics, these include biostatistics, optimal design, computer experiments, sequential analysis, shape-constrained inference, time
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of statistical analyses, in particular: Exploratory and confirmatory factor analysis, Multilevel analyses (including latent class analysis), Time series analysis, Bayesian inference methods, Regression techniques