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three scientific research departments, themselves organized into teams. The PhD will take place more specifically within the MAORE team, whose members use tools from combinatorial optimization, graph
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CeMM - Research Center for Molecular Medicine of the Austrian Academy of Sciences | Austria | 3 days ago
to develop your innovation and entrepreneurship skills at the cutting-edge of AI/ML and biomedical research? If yes, apply now of our 15-20 fully funded PhD positions here: https://apply.cemm.at/ Supported by
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the use of hierarchical graph neural networks for modeling multi-scale urban energy systems. By combining advances in Physics-Informed Machine Learning (PIML) and Graph Neural Networks (GNNs) with real
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Stig Brøndbo 18th January 2026 Languages English English English Faculty of Science and Technology PhD fellow in “LLMs based Knowledge Graphs towards Digital Twin Development in Green Shipping
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The AITHYRA-CeMM Joint International PhD Call in Molecular Medicine and Artificial Intelligence (m/f
-20 fully funded PhD positions here: https://apply.cemm.at/ Supported by the Medical University of Vienna, the Technical University of Vienna and University of Vienna, the AITHYRA and CeMM PhD programs
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FOR DRAWING UP OF PREDOCTORAL CONTRACTS FOR THE TRAINING OF DOCTORAL STUDENTS FUNDED BY THE UPV'S RESEARCH STRUCTURES – SUBPROGRAMME 2 (PAID-01-22) 119865 Development of machine-learning and graph-based models
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AI-driven tools for bio-retrosynthesis-based metabolic pathway design, enzyme design and optimization, and DNA part selection. 2) knowledge-graph-based combinatorial experiment designs are used to span
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Tomon. More information about Discrete Mathematics at Umeå University can be found on the group’s homepage: https://www.umu.se/en/research/groups/discrete-mathematics/ As a PhD student, you will be part
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applications will be probed in order to validate the implementation of these techniques in key computer vision-related tasks, such as image classification, multimodal data generation, or manipulation of graph
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the response model from reactive to proactive. The goal is to increase transparency and trust in the DNS namespace. Key research activities will include applying machine learning and graph-based techniques