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Probabilistic Circuits. Causal Representation Learning. Causal Explanations. Causality and Large Language Models. Counterfactual learning. Job requirements Master’s degree in Computer Science, Mathematics, or a
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motivated and skilled PhD candidate to work in the area of probabilistic machine learning. The position is fully funded for a term of four years. The research direction will be determined together
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models. Trustworthy AI is a major topic in machine learning, which is illustrated by the increasing number of initiatives to enforce AI systems to be more trustworthy. Although machine learning models
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Irène Curie Fellowship No Department(s) Applied Physics and Science Education Reference number V34.7526 Job description Are you inspired by combining physics-based models with machine learning
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) collaborating with machine learning experts (a second PhD student in USA) integrating personalised AI into meaningful assistive technology interventions (4) critically evaluating methodological approaches in
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for compositional methods that focus on extra-functional aspects, such as performance, resource budgets, security, or energy, pursuing hybrid, knowledge-driven and machine-learning-based, approaches. As a newly
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machines are commonly used in electric vehicles. However, these machines have several disadvantages, such as the high cost of the permanent-magnet (PM) material and decreased performance at higher
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machine learning; a minor in mathematics is a plus; A strong interest in data mining research with focus on local pattern mining, exceptional model mining, or related techniques. Data mining software
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English. An aptitude for independent work. A background in computer science, especially machine learning, is a plus. Conditions of employment A meaningful job in a dynamic and ambitious university, in
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computing, advanced machine learning applications, and the deployment of 5G and future 6G systems, the size and traffic of data centers is steadily growing. The proliferation of data centers and the need