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. Essential qualifications and experience a PhD (or near completion) in one of the following fields (or a closely related discipline): Computer Science, Artificial Intelligence, or Machine Learning Economics or
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/or peer-reviewed journals Required Knowledge, Skills, and Abilities: PhD in Computational Physics, Chemistry, Materials Science, Computer Science/Engineering, Applied Mathematics, or a related field
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researcher will work at the interface of root developmental biology, 3D modeling, network and graph theory, and data analysis, in close interaction with biologists, modelers, and computer scientists (INRAE
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positions for distinguished professorship. Candidates in areas including, but not limited to, Algebra, Number Theory, Geometry, Topology, Combinatorics, Graph Theory are encouraged to apply. Responsibilities
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the period of the project, not exceeding the maximum period set by FCT for such grants. RENEWAL Renewable is subject to performance if the candidate is enrolled in a PhD program - art. 6º, n.4 c) https
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to capture the spatial complexity of tumor organization and its relationship to treatment response. This PhD project aims to develop robust multimodal predictive models of platinum resistance using a large
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/knowledge graphs, and carbon accounting. The Research Fellow will help develop and lead the CognitionX Lab (https://cognitionx-lab.github.io/ ) with Dr. Jinying Xu, Assistant Professor and Director of
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) Your main responsabilities : To carry out research missions in the field of graph generation under constraints To ensure supervision and tutoring missions To contribute to the reputation of the School
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, and clinical safety datasets Implement graph-based retrieval-augmented generation (RAG) methods to enhance knowledge extraction and information synthesis Develop cross-pathway analytical methods using
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. A particular focus of the project will be on: 1) Graph Neural Networks for cosmology, neutrino and/or collider physics, 2) Domain adaptation methods / model robustness, 3) Uncertainty quantification