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for Clean Energy Conversion: Learning Multiscale Dynamics in Fuel Cell Systems”. The project aims to develop a multiscale modeling framework that combines computational fluid dynamics (CFD), electrochemical
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deformation microscopy, high-field MRI, clinical MRI, PET-MRI, and molecular read-outs. •Applying inverse finite element modeling (FE modeling) for the multiscale mechanical characterization of cartilage
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will develop and exploit mesoscopic, and multiscale computational models to assist medical applications of ultrasound-guided drug and gene delivery and imaging. The project focus are the encapsulated
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strategic programme. Through multiomic and spatial biology exploration of temporally distinct samples from clinical trials and advanced biological models, an international consortium of leading colorectal
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and core logging focused on structural geology of the Meskala basin. This will involve a thorough structural analyses, multiscale stress and strain characterisation, analysis of hydrocarbon reservoirs
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, are needed. Specific expertise can focus on modelling of e.g., polymer, biomolecular systems, or colloidal systems. We work at both atomistic and coarse-grained modelling levels and appreciate multiscale
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project aims to develop model vitrimer systems produced in powder form (at the CP2M laboratory) and to understand the fundamental mechanisms of stress-assisted sintering, a central process for achieving
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the supervision of Dr. Joseph Kwon. We’re seeking a creative Postdoctoral Scholar to join our team and advance cutting-edge multiscale and hybrid modeling—integrating first-principles simulations with
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | about 5 hours ago
Biology Dresden (CSBD) are basic research institutes that pursue a mission to advance multiscale biological discovery using interdisciplinary approaches including innovative, cutting-edge mathematics
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new NIH-funded Center for Excellence in Multiscale Immune Systems Modeling. This position focuses on leveraging and developing new equation learning methods, such as Physics-Informed Neural Networks