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, school-level aggregated data, and genetic data. The successful candidate is expected to use state-of-the-art research methods for drawing causal inferences from non-experimental data. The successful
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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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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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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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well as having a strong track record in relation to computational efficiency, which is fundamental in real time processing of streaming data. The main purpose of a postdoctoral fellowship is to provide
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. FATES simulates and predicts growth, death, and regeneration of plants and subsequent tree size distributions by tracking natural and anthropogenic disturbance and recovery. It does this by allowing
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spoken English) . It is preferable that the candidate has (and can document): a strong academic track record experience in collection-based research (both physical and/or digital) teamwork and networking
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defense are eligible for appointment. Fluent oral and written communication skills in English. A strong track record in fundamental research in modelling of biophysical phenomena, capillary flows or wetting
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MIMICS+ module for soil carbon decomposition. FATES simulates and predicts growth, death, and regeneration of plants and subsequent tree size distributions by tracking natural and anthropogenic disturbance