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Field
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critical thinking and problem-solving skills. Outstanding presentation skills. Experience in graphing, statistical analysis and data management skills. Proficient in Word, Excel, GraphPad, Adobe Photoshop
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Graph neural networks Generative models (VAEs, diffusion models) Multi-modal learning Knowledge of bioinformatics tools and data formats (FASTQ, BAM, VCF, H5AD, AnnData, Seurat, etc.). Experience with HPC
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Postdoctoral Positions for Computational Genomics, Cancer Genetics, and Translational Cancer Biology
immunotherapies, integrating graph neural networks, regulon-aware pooling, and transfer learning with biological regulatory networks. 4) Developing and validating computational biomarkers (IGR burden, TAA burden
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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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, for their analysis and optimization, we use tools such as artificial intelligence/machine learning, graph theory and graph-signal processing, and convex/non-convex optimization. Furthermore, our activities
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-doctoral associate to work on one or more of the following topics: Mathematical Physics, Spectral Theory, Quantum Chaos, Large Graphs and Quantum Walks. Related areas such as Quantum Information can also be
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language models to whole genome sequencing data - Develop algorithms and neural network architectures for the prediction of structured outputs (i.e. trees, graphs) - Implement and develop methods
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inequalities and Sobolev-type spaces (with Hytönen and/or Korte), 3. Conformal deformations of metric measure spaces and/or general regularity and convergence for graph-based machine learning using stochastic
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and machine learning. Topics of interest in this area include, but are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge
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are not limited to: natural language processing, large language models, graph learning, prompt engineering, knowledge graphs, knowledge engineering, linked data, web technologies. About the role