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University of Technology (TU/e)CountryNetherlandsCityEindhovenPostal Code5612 APStreetDe Rondom 70Geofield Where to apply Website https://www.academictransfer.com/en/342216/phd-position-in-causal-machine-learn
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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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cutting-edge Machine Learning/AI techniques to real-world problems? The Scalable computing group are focused on applying Machine Learning/AI and visualisation to real-world problems – highlighted by
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, scalability, interpretability, and explainability of AI. The UAI group is looking for a highly motivated and skilled PhD candidate to work in the area of probabilistic machine learning. The position is fully
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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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the development of artificial systems that each integrate different aspects of machine learning, multimodal sensing, ubiquitous computing and social science. In addition, the successful candidates will have the
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Skip to main content. Profile Sign Out View More Jobs PhD scholarship in Machine Learning in IoT Edge Devices – DTU Electro Kgs. Lyngby, Denmark Job Description We invite applications for a PhD
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-generating mechanism, integrating it with recent insights from debiased machine learning and causal inference. Besides laying foundations for a novel paradigm for causal/statistical modeling, this project
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A four-year PhD Studentship in Pharmacometrics and Machine Learning funded by the UKRI EPSRC and GSK is available within the Institute for Global Health. The studentship will commence from 1st
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to computational cardiology. In this project, you will combine advanced physics-based models of the human heart and vasculature with the latest breakthroughs in machine learning to develop scalable and robust