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to predict memory accesses and anticipate page faults. At present, it is almost impossible to execute AI models in kernel space, since floating-point operations—required by AI workloads—are not supported
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Infrastructure? No Offer Description The postdoctoral researcher will contribute to the ANR-funded Pi-CANTHERM project, which aims to design, model, and predict the performance of new n‑type organic thermoelectric
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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | about 4 hours ago
multi-expert segmentation databases. The postdoctoral fellow will focus on integrating segmentation variability into deep learning models, with the goal of assessing prediction reliability and enabling
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and localization of a potential fault using the Matched Field Processing (MFP) method, based on the reconstruction of a response model of the inspected structure from the modal parameters predicted by
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The successful candidate will be responsible for: 1. Develop the numerical and analytical tools required to design these tunable random architectures and predict the mechanical behavior
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performance of diagnostic tests when these tests are imperfect. The case of plague in Madagascar in 2017. ten Bosch et al, PLoS Biology 2022 Development of an ensemble model to forecast COVID-19
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, · quantifying uncertainty in causal links, · integrating the resulting models into neural networks (or other machine learning models) to detect and predict anomalies or anticipate failures. The research
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Postdoctoral position: Developing a human lymphoid organ-on-chip to evaluate candidate mRNA vaccines
Chakrabarti at the Pasteur Institute in Paris. The position is fully funded for 3 years in the frame of an industrial contract. Predicting the immunogenicity of candidate vaccines in humans remains a challenge
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health and translational medicine using a "bench-to-bedside" approach. By harmonising and analysing diverse biomedical data, while focusing on the secure data processing and predictive modelling, we aim
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) exhibit persistent dose-dependent m6A methylation levels and may serve as biomarkers of radiation exposure [12]. m6A methylation may also be used to predict radiation sensitivity [13] or to develop new