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Field
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for sequence or structural data (e.g. transformers, graph neural networks) Proved experience in working independently and as part of a multidisciplinary team Evidence of strong communication and scientific
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development experience GTSAM or similar factor graph optimization frameworks Field robotics deployment in challenging environments Multi-sensor calibration and fusion Commitment to open-source development and
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quantum information theory, algebraic topology, polyhedral combinatorics, graph theory, and optimization are strongly encouraged to apply. For more details on the project, visit open positions page . To be
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | about 2 hours ago
with biomedical data, including clinical, EHR, omics, and imaging Knowledge graphs (KGs), and integrating LLMs with KGs Multimodal LLMs Special Physical/Mental Requirements Special Instructions
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Lab (MaTRIX Lab) develops advanced computational and AI methodologies to decode complex biological systems and accelerate discoveries into translational impact. The lab integrates deep learning, graph
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of the Postdoc Research Fellows are the following: Research: Work on novel AI/Data Science research with crucial interdisciplinary scope using machine/deep learning, generative/agentic AI, and knowledge graphs
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accuracy in link-tracing designs (e.g. Respondent driven sampling) Partial graph data collection strategies for networks (e.g. Aggregated Relational Data) Large scale models for anomaly detection on graphs
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CBS - Postdoctoral Position, Artificial Intelligence Applied to Metabolomics for Health Applications
metabolomics data from clinical studies. Apply deep learning models (e.g., autoencoders, variational autoencoders, graph neural networks) for biomarker discovery, disease classification, and patient
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the Science Division, New York University Abu Dhabi, seeks to recruit a post-doctoral associate to work on one or more of the following topics: Mathematical Physics, Spectral Theory, Quantum Chaos, Large Graphs
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computer science using data-driven techniques (graph theory, ICA, machine learning), in other imaging modalities (DTI; MEG), and in multimodal integration will be relevant. Experience with AFNI/SUMA, SPM, FSL