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data reflect real‑world disease phenotypes. Advanced analytics: apply AI and machine‑learning techniques (e.g., graph neural networks, multimodal transformers) to uncover novel biomarkers and generate
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present results from your research and develop your network. In addition to your own research and experiments, you will also supervise and help train new students when they join the group. This will help
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prior to the application deadline Research experience with deep learning architectures (e.g. Transformers, diffusion models, graph neural networks) applied to multimodal data. Proven expertise in time
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-smokers. The successful candidate will have a leading role in the analysis of bulk- and single cell RNA-seq data, miRNA seq data from scarce particle samples, multi-omics integration and network medicine
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combination with machine learning and/or data mining techniques • Explainable AI/ML using visualization • AI/ML-empowered visual analytics of multivariate networks (network embeddings, …) • Large Language Model
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combination with machine learning and/or data mining techniques • Explainable AI/ML using visualization • AI/ML-empowered visual analytics of multivariate networks (network embeddings, …) • Large Language Model
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collaboration with Olof Lagerlöf’s group. The postdoc will image (and influence with opto-chemogenetics) the network representation of stimuli of different economic/hedonic value and its plasticity with two
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an integrated development of network architectures, resource efficient algorithms, and programming paradigms for enabling an application-tailored design of dependable communication and computation systems
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build the sustainable companies and societies of the future. Subject description The research subject focuses on an integrated development of network architectures, resource efficient algorithms, and
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of progenitor-to-tumor cell niche transitions, focusing on the esophageal epithelium. Duties The current project will be centered around characterizing changes in local cell-cell networks during early esophageal