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IFREMER - Institut Français de Recherche pour l'Exploitation de la MER | Brest, Bretagne | France | about 8 hours ago
are currently retreating and are predicted to further shrink into the 21st century. Reductions in sea ice have major implications on the climate, the ecosystems, and on human societies. Reliable
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, as well as doctoral students, post-doctoral fellows, interns and/or volunteers. More details on https://tourduvalat.org/en/ Background and objectives Climate change is a major pressure on ecosystems
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). The grant aims to develop and implement the following activities: 1) Monitoring the implementation of the "NIZO" project, within IPC tasks; 2) Predictive analysis; 3) Development and implementation
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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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to correct or account for these biases, and build predictive models that simulate biological responses to in silico perturbations such as genetic or pharmacological interventions. The project aims to advance
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and with the 2AT team at Institut Pprime to develop an innovative jet-noise prediction tool. The researcher will develop a novel jet-noise prediction tool based on a resolvent analysis of the Navier
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model introduced previously for carburizing will be further developed in this study. In this model, carbon diffusion is predicted using Fick's law and finite difference scheme. A source term accounts for
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. The candidate will calculate misfit values between the statistically modeled RSL and glacial isostatic adjustment (GIA) model predictions of RSL to identify modifications to the ice history and Earth parameters
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to accelerate the path to certification. More details on the project can be found here: https://hecustom.eu/ This post will contribute to the creation and validation of a digital twin (with biological bone models
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partnerships with government agencies across the United States. PRIISM is an interdisciplinary center that builds capacity for researchers within academia and beyond to collect data, build inferential models and