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Your Job: Chromatography modeling, while crucial for modern bipporcess development, still heavily relies on empirical determination of key model parameters. By combining protein structure
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data sets, which have to be evaluated in order to obtain a holistic understanding of very complex systems. Visit HDS-LEE at: https://www.hds-lee.de/ Your tasks in detail: Review existing literature
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Midlands Graduate School Doctoral Training Partnership | Loughborough, England | United Kingdom | about 1 month ago
of Nottingham to commence in October 2026. Project overview This project investigates how housing inequalities spatially structure wellbeing in cities. It begins from the premise that where we live — and the
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heavily relies on empirical determination of key model parameters. By combining protein structure descriptors, molecular simulations, and machine learning, this PhD project seeks to predict ion-exchange
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will enable predictive simulations of structural, thermodynamic, and kinetic properties in complex systems relevant to catalysis, supramolecular chemistry, and biology. The candidate will benefit from
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advances the Center’s mission to create an affirming, responsive, and data-informed campus environment. Essential Functions: Develop and pilot surveys, focus groups, and structured interviews to evaluate
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algorithms Extend the superstructure to tackle AC-PF problems of different complexities and assess its convergence in inference Investigate scaling and performance bottlenecks Explore hybrid ML-classical
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explicitly extend these models to capture temporal structure within spike trains thereby moving towards analyses that are sensitive not just to firing rates but also precise timing relationships underpinning
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geometries. Current simulation-based approaches require complex 3D meshes and are often too slow for practical medical use. This project aims to create accurate and rapid surrogate models by combining physics
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population-level neural interactions. Prior work has emphasized rate-based codes due to their relative simplicity; our approach will explicitly extend these models to capture temporal structure within spike