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of economics of innovation and the economics of ICTs / AI. Experience with one or more of the following empirical research methods will be considered an advantage: applied microeconometrics and causal inference
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methods to draw causal inferences from non-experimental data. The main data source is administrative register data linked with large-scale survey data and genetic data. The successful candidate should have
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an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the following computing skills will be considered an advantage: Natural
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an advantage: applied microeconometrics and causal inference; machine learning and data science. Experience with one or more of the following computing skills will be considered an advantage: Natural
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data, computationally intensive inference for complex models, causal inference and survival models, measurement uncertainty, and research for clinical trials and observational studies - and numerous
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, with interests spanning a broad range of areas - including statistical machine learning, high-dimensional data and big data, computationally intensive inference for complex models, causal inference and
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appropriate conditions, it provides a confidence set (credibility set if prediction is Bayesian) for a multivariate estimate with statistical coverage guarantees. This PhD project aims to develop new CP methods
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predictions. To mitigate these effects, advanced ML techniques such as Bayesian deep learning, probabilistic models, and uncertainty quantification methods can be applied to enhance model robustness
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academic achievements in previous studies. Demonstrated knowledge of statistics and causal inference methods / econometrics, including good results in advanced courses. Experience with programming and
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planning and make such systems more reliable. BaneNOR are responsible for the Norwegian rail infrastructure and oversees operations, maintenance and construction of railways throughout the country