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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 9 days ago
the machine learning community as challenging, high-dimensional testbeds. Notably, the recently developed WOFOSTGym simulator \cite{solow2025wofostgym}, bridging crop modeling and RL, received the Outstanding
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Inria, the French national research institute for the digital sciences | Palaiseau, le de France | France | 27 days ago
. [9]). We are particularly interested in improving the selection of transmission opportunities (e.g., using precomputed sequences), possibly constructed with machine learning techniques (as in [8]). We
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are looking for a motivated postdoc with solid experience in bioinformatics and in machine learning. The position centers on SRPs and LLPS, and the successful candidate will contribute to several ongoing
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at the interface of biological physics, agent-based simulations and machine learning to turn quantitative imaging data into a mechanistic, testable model of spindle positioning. In particular, we expect
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team at the Laboratoire d'Informatique de Grenoble (LIG). GetAlp conducts research in NLP, machine learning, evaluation, and interpretability. The project will be supervised by Maxime Peyrard (CNRS
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, involving expertise in optics, electronics, image and data processing, chemistry, and biology. With the support of several European funding programs, the team is building a data science and machine learning
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Machine/Deep learning and classification Knowledge of the Linux operating system for using a computing cluster Interest in transdisciplinarity and teamwork Autonomy and scientific rigor Website
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conceptual DFT (linear response function, Fukui functions) or QTAIM theory (delocalization index), and their validation on a set of compounds known from the literature - interfacing a MLIP (Machine-Learned
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Requirements Research FieldComputer science » Computer systemsEducation LevelPhD or equivalent Skills/Qualifications Knowledge • Solid understanding of machine learning, deep learning, and modern AI techniques
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on the plants Arabidopsis thaliana will generate maps of depolarization, retardance, dichroism, and optical axis azimuth, which will feed machine learning models developed by the project partners to identify