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during surgery or endoscopic exploration. This postdoctoral position aims at developing innovative deep learning algorithms to help histology classification. Both classical histology based on hematoxylin
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Single-cell high-throughput sequencing technologies generate unprecedented volumes of molecular data at cellular resolution, opening new avenues for the application of machine learning
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16 Mar 2026 Job Information Organisation/Company Université de Haute-Alsace Department IS2M Research Field Chemistry Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 5 May 2026 - 12:00 (Europe/Paris) Country France Type of Contract Temporary Job...
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machine learning (ML) approaches offer a powerful framework for modeling complex catalytic materials with near ab initio accuracy while enabling simulations at significantly larger spatial and temporal
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Sorbonne Université SIS (Sciences, Ingénierie, Santé) | Paris 15, le de France | France | about 1 month ago
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of the ERC Consolidator project AUTOMATIX (see details below), we are seeking a PhD candidate to develop machine learning approaches for constitutive modeling. Context With the advent of machine-learning (ML
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French National Research Institute for Agriculture, Food, and the Environment (INRAE) | Montpellier, Languedoc Roussillon | France | 2 months ago
with skills in statistics and modelling through machine learning (Agronomy joint research unit, MIA joint research unit, Wageningen University & Research); (ii) national and international laboratories
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. 132, no. 3, pp. 1521–1534, 2012. [6] S. Koyama, J. G. C. Ribeiro, T. Nakamura, N. Ueno, and M. Pezzoli, “Physics-informed machine learning for sound field estimation: Fundamentals, state of the art, and
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of molecular data at cellular resolution, opening new avenues for the application of machine learning to fundamental biological problems. The postdoc (M/F) to be recruited to join the Machine Learning
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mechanics, finite element modeling, and scientific machine learning. The RSE will contribute to the design, implementation, and maintenance of open-source software libraries that integrate phenomenological