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developed countries, smartphone penetration exceeds 80%. The automatic transport mode detection (TMD), when effectively exploited, possibly using some kind of machine learning algorithm, provides more
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to machine learning algorithms in order to get uncertainty estimates for parameters governing the distribution of the observed data. The predictive Bayes scheme for uncertainty quantification contains a wide
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questions and data of CREATE. The successful candidate will conduct advanced methodological and psychometric research. Potential topics include (a) AI, machine learning, and large language models
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processes based on mobile digital technologies increase, so do the amount and severity of cyber threats. Both defenders and attackers are now using Machine Learning (ML) and Artificial Intelligence (AI
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: simulation and risk modelling using advanced statistical and machine learning based methods. strategic portfolio management and dependency structure modelling for financial assets. effects of climate change
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, Mathematics (Operations research) or Computer Science or Machine Learning). The master thesis must be included in the application. Documented proficiency in English, please see requirements below. Requirements
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, you will conduct cutting-edge research in these areas. You will learn state-of-the-art techniques in formal methods and knowledge representation and apply them to high-impact use cases related
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related to models and multiple sources of data describing ecological dynamics. The PhD project will address the following aims: 1) Develop efficient tools for learning about models from data, 2
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Environment Convergence Environment. Clim-SHOCK investigates volcanic climate shocks from the past and places them into a future scenario. What can we learn from the past to improve future climate projections
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) to enhance AML capabilities. AI-driven solutions can learn from vast datasets to spot hidden patterns and anomalies beyond human or rule-based detection. For more information and how to apply: https