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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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: - Apply unsupervised machine learning concepts to the analysis of continuous seismograms recorded in the vicinity of active volcanoes, in order to extract information about the state of the volcano and the
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enabling the construction of the most compact and powerful electrical machines. The project will combine recycled NdFeB raw materials with the production freedom of additive manufacturing (AM) technologies
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specialized in Technology-Enhanced Learning (TEL) and Human-Computer Interaction (HCI). In particular, SICAL has extensive experience in behavior analysis using multimodal data in different contexts, including
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vision projects using computer vision libraries (OpenCV), machine learning frameworks (Pytorch and Tensorflow) Good understanding of ROS, ROS2 (Robot Operating System) and ability to work on Linux
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in the field of medical imaging. The team particularly studies the potential of machine learning methods for an efficient and relevant representation of medical data such as images. The challenges
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: Conducting research on perception and situation understanding, making contributions to the state-of-the-art in the fields of simultaneous localization and mapping (SLAM), computer vision, machine learning
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multidisciplinary environment, the candidate will work on the development of novel methods for analysis of state-of-the-art spatially resolved data. The candidate will explore the landscape of explainable machine
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more than one year (or part-time equivalent) are NOT eligible to apply for an award. Recommended reading https://www.england.nhs.uk/2019/06/nhs-aims-to-be-a-world-leader-in-ai-and-machine-learning-within-5