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and Energy (HDS-LEE), the project offers an interdisciplinary research environment at the interface of bioengineering, computational biophysics, and data-driven modeling, with strong links to open
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Your Job: This PhD project develops a Bayesian inference framework for hybrid model- and data-driven modeling of metabolism, with a particular focus on handling model misspecification. By combining
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Your Job: We are looking for a PhD student to develop learning-based surrogate models for predicting stress fields in patient-specific arteries. Especially high stresses in plaque can lead to
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for a highly motivated PhD candidate to join our world-leading research program in Earth System modelling and improving Earth System Modeling by better merging of measurement data and model simulations
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of bioengineering, computational biophysics, and data-driven modeling, with strong links to open-source software development and industrially relevant applications. Tasks include: Development of molecular descriptors
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partner is possible Unique HDS-LEE graduate school program (including data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ Qualification that is highly welcome in
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scientific advisors and opportunity to mentor students Unique HDS-LEE graduate school program (including data science courses, soft skill courses and annual retreats): https://www.hds-lee.de/about/ A
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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Germany Type of Contract To be defined Job Status Other Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research
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the comprehensive training programme of the graduate school HDS-LEE https://www.hds-lee.de/ A structured doctoral degree programme via our doctoral researchers’ platform JuDocs https://www.fz-juelich.de/judocs