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imaging, computer vision, and predictive modelling. The postdoc will further develop an existing rumen‑fill scoring algorithm into a functional prototype and pilot the technology for longitudinal monitoring
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the occupational risks faced by inhabitants of the Roman Empire influenced their choice of preferred cults. The main methods used in the project include spatial analysis, predictive modelling, statistics, and the
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or biases in data collection, storage, and processing pipelines. Additionally, the candidate will develop AI models that can adapt to dynamic and evolving data environments, incorporating mechanisms
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. Our mission is to move beyond descriptive biology and develop predictive, mechanistic models that connect molecular regulation to cellular and systems-level phenotypes. The Laboratory of Computational
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-related challenges in maritime transportation systems; 2) supporting the development and application of quantitative and data-driven models for assessing and predicting risks and system performance; and 3
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Centre de Mise en Forme des Matériaux (CEMEF) | Sophia Antipolis, Provence Alpes Cote d Azur | France | 3 months ago
Infrastructure? No Offer Description The aim of this PhD is to model the development of microstructures during welding processes on thick parts, in the context of nuclear equipment, for which deposits of several
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particle clustering and morphology affect strain localization and damage evolution. Integrate experiments and modelling to create predictive tools for recycled alloy performance. Your immediate leader is
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trends and composition analysis, refractive index determination, and morphology for applications such as environmental monitoring, nuclear non-proliferation, and improving predictive modeling tools (e.g
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applied in particular to the modeling of 3D-printed concrete at the Navier laboratory, to better predict complex phenomena such as material curing and crack formation. Where to apply E-mail jeremy.bleyer
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learning methods (e.g., predictive modelling, clustering, multivariate integration) to large-scale time series and sensor datasets. Contributing to the development of risk models and decision-support tools