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simulations, and is designed to conduct Bayesian parameter inference; semi-analytic jet and accretion modelling codes (in C++, with a Python interface) that are being integrated into the open-source Gammapy
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areas include: machine learning foundations, generative modelling, foundation models, cross-domain/-modality learning, explainable AI and mechanistic interpretability, representation learning, Bayesian
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areas include: machine learning foundations, generative modelling, foundation models, cross-domain/-modality learning, explainable AI and mechanistic interpretability, representation learning, Bayesian
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Research Assistant (m/f/d) with a Ph.D. in Civil Engineering, Engineering Physics, Physics, Mathemat
(e.g., DeepONet, Fourier Neural Operators) Knowledge of uncertainty quantification, inverse problems, Bayesian inference, or parameter identification In addition you have: A high degree of initiative and
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faculty with teaching experience outside of India. The faculty is expected to teach courses such as: Probability and Statistics Mathematical Statistics Statistical Inference Regression Analysis
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modelling, reactor physics or nuclear engineering, numerical modelling of heat transfer, material behaviour or solid mechanics, Bayesian inference, model calibration, and Markov Chain Monte Carlo methods
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analysis Structural equation modeling Bayesian data analysis Multivariate statistical methods Longitudinal data analysis Causal inference methods Demonstrated ability to select and apply appropriate
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expertise include but are not limited to health economics, policy analysis, implementation science, geospatial analysis, biostatistics and research design, AI analytics, agent-based modeling, Bayesian
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candidate will join a growing collaborative research environment at UiA focused on robust inference about ecological and evolutionary change in human-influenced systems. Researchers work with complex data
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, although not limited to, the design of clinical trials, observational studies, longitudinal and survival analysis, epidemiologic modeling, Bayesian analysis, modern causal inference, biomarkers