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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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Doctoral candidate (PhD) – Computational Biomedicine / Machine Learning / Spatial Omics (m/f/d) Stellenanzeige merken Stellenanzeige teilen starting 01.09.2024 at the Institute for Computational
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available from 1 October 2024 or later. You can submit your application via the link under 'how to apply'. Title PhD position in machine learning to predict nitrogen leaching at field level Research area and
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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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. Work in the group involves using machine learning and omics data analysis to gain insights into biological systems, including cancer cell plasticity, immune response, and pattern formation in development
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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