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Inria, the French national research institute for the digital sciences | Saclay, le de France | France | 3 months ago
(or surrogate models) are approximations of classical numerical solvers with a very low computational cost. They form the core of a digital twin. Using machine learning techniques to build these meta-models
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processes for manufacturing large area meta-materials. In particular, we will focus on roll-to-roll (R2R) processing methods, which we seek to combine with emerging bottom self-assembly processes and top-down
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(meta-)genomes Experience in the computer-assisted analysis of large biological datasets (e.g., using R, Python, and Bash/Linux environments) Very good written and spoken English skills Ability to work
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or environmental monitoring; Collect, manage, analyse, and interpret data using transparent and reproducible workflows; Conduct evidence synthesis, meta-analysis, comparative analyses, or environmental modelling
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relevant, field sampling or environmental monitoring; Collect, manage, analyse, and interpret data using transparent and reproducible workflows; Conduct evidence synthesis, meta-analysis, comparative
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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
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, materials, and synthetic cells with embodied intelligence – chemical and physical – to endow them with the capacity to compute, adapt, learn, or make simple decisions. We are highly international and
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Synthetic Cells as Minimalistic Life Forms," Nature Reviews Chemistry 8, 454 (2024). R. Merindol, A. Walther, "Materials Learning from Life: Concepts for Active, Adaptive and Autonomous Molecular Systems
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national PhD scholarship. Additional support is available for project resources and conference attendance. Be inspired, every day Drive your own learning at one of the world’s top 80 universities Take your
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metabolism and function in diabetic cardiomyopathy (DbCM). The project combines cardiovascular physiology, molecular biology, metabolism, and translational research within the international SHEA-META