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aggregates in biological fluids. The project aims to develop and refine a cutting-edge single-molecule detection platform that leverages molecular amplification and nanoscale sensing to identify and
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: Writing scientific articles and presenting results at conferences. Candidate profile PhD in Applied Mathematics, Fluid Mechanics, or a related field. Strong programming skills in C++. Experience with IGA
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strong expertise in statistical physics, soft/condensed matter theory or continuum mechanics of fluids or solids? The Max Planck Institute for the Physics of Complex Systems (MPI‑PKS) in Dresden announces
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/ Biology , Biological Physics , Biophysics , Biophysics/Soft Condensed Matter Theory , Condensed Matter Theory , evolution , Fluid Physics , Material Science , Mechanical Engineering , Network , Nonlinear
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Max Planck Institute for Solar System Research, Göttingen | Gottingen, Niedersachsen | Germany | 17 days ago
turbulence are fundamental problems in geophysical and astrophysical fluid dynamics. This project will focus on understanding the nonlinear dynamics of rotating flows and turbulent transport, with applications
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the following skills: Professionnal skills: - Solid grounding in reactive fluid mechanics and materials - Ability to analyse complex phenomena and interpret experimental results Personal skills : - Ability
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of reactions between the metal-bearing hydrothermal fluid and organic carbon. The task will implement an innovative methodology integrating in-situ spectroscopy and physicochemical modeling. Through
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of the Research Institute, New York University Abu Dhabi, seeks to recruit a Post-Doctoral Associate to work in the fluid mechanics laboratory for experimental fluid dynamics. SITE is inviting
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to: Setup, validation, and evaluation of Computational Fluid Dynamic (CFD) models for the elucidation of bioreactor heterogeneities and performances Development and application of modelling/simulation
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well as interpretability of scientific foundation models. The rush to build foundation models has led to the development of large machine learning models in Astrophysics, fluid dynamics, biology, weather prediction, solar