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the use of large language models to support neural network design and data preprocessing. The position involves close collaboration with experts in cardiovascular simulation and Scientific Machine Learning
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Your Job: Develop methods and workflows to construct robust co-regulation networks from large single-cell and spatial transcriptomics datasets Integrate ontologies and metadata (e.g., tissue, cell
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19 Jan 2026 Job Information Organisation/Company Forschungszentrum Jülich Research Field All Researcher Profile First Stage Researcher (R1) Application Deadline 19 Jan 2038 - 03:14 (UTC) Country
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network approaches for stress prediction in arterial walls and plaque. Another part of the project is exploring the use of large language models to support neural network design and data preprocessing
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into the open-source CADET simulation framework, enabling fully predictive process simulations without extensive experimental calibration. Embedded in the Helmholtz Graduate School for Data Science in Life, Earth
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19 Jan 2026 Job Information Organisation/Company Forschungszentrum Jülich Research Field All Researcher Profile First Stage Researcher (R1) Application Deadline 19 Jan 2038 - 03:14 (UTC) Country
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19 Jan 2026 Job Information Organisation/Company Forschungszentrum Jülich Research Field All Researcher Profile First Stage Researcher (R1) Application Deadline 19 Jan 2038 - 03:14 (UTC) Country
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19 Jan 2026 Job Information Organisation/Company Forschungszentrum Jülich Research Field All Researcher Profile First Stage Researcher (R1) Application Deadline 19 Jan 2038 - 03:14 (UTC) Country
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. Thus neuronal experimental data are to be analyzed for both aspects by PCA analysis and statistical multivariate methods to extract spatio-temporal spike patterns. Finally both results will be linked and
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while maintaining clarity in the interpretation of results. Concurrently, AI-based methods are developed that prioritize interpretability and reduce data dependency by imposing desirable constraints