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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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isotherm parameters directly from molecular properties. These predictions will be integrated into the open-source CADET simulation framework, enabling fully predictive process simulations without extensive
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information about our institute here: https://www.fz-juelich.de/en/ias/ias-8 Your Job: Develop physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic
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optimise the developed methods on real biological datasets; work closely with experimental partners for interpretation and validation of results Contribute to the integration of the developed methods
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model predictions Writing of the thesis and publication about the relation of experimental data and model results Your Profile: A Masters degree with a strong academic background in physics, mathematics
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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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a project linked to the “Helmholtz School for Data Science in Life, Earth and Energy (HDS-LEE)”. Your Job: Develop physics-aware simulations of growing cell populations, including their spatiotemporal
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(guilt-by-association), and benchmark them against existing bulk co-expression resources Compare and optimise the developed methods on real biological datasets; work closely with experimental partners