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regularly in its various training and research activities, as well as the weekly seminars in IDAEA-CSIC. Where to apply Website https://www.idaea.csic.es/job-offer/phd-position-understanding-and-predicting-n
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of the MOST (Modelling and Simulation of Turbulence) team focus on the numerical prediction of turbulent and multiphase flows with a broad range of objectives from fundamental understanding of flow properties
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have access to state-of-the-art facilities, including cleanroom microfabrication, laser micromachining, 3D printing, advanced microscopy, and numerical modeling tools. The project benefits from a close
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translational model based on patient-derived tumour organoids that reproduce the realistic microanatomy of the tumour. These organoids will be used for translational testing of nanotherapeutic activity
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the development of highly predictive and human-relevant biomedical models that overcome major limitations of conventional animal models. The recruited candidate will focus on the development of an advanced human
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developing simulation flows, analysis methodologies, and predictive models that enable Design-Technology and System-Technology Co-Optimization (DTCO/STCO) studies for future systems. You will work closely with
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wireless system. Analyse experimental measurements using MATLAB, Python or equivalent computational tools. Compare experimental measurements with modelling or theoretical predictions generated by the wider
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PhD students. The MoM section is recognized worldwide for its high-level research on experimental analysis, theoretical understanding and predictive modelling of complex thermo-mechanical behaviour (e.g
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. This includes extending or adapting existing scenario modelling approaches to support increasingly complex cybersecurity exercises. RO3: Investigate simulation and predictive modelling approaches
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interferometry, etc.), (v) Predictive modelling of coupled phenomena (reactive transport, rock-water interactions, etc.), (vi) Uncertainty quantification (Monte Carlo, meta-modelling), and (vii) Risk analysis. The