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The Computer Vision Group is looking for an aspiring PhD to investigate multi-agentic AI, LLMs, and VLMs applied to agricultural sciences. Currently, established AI models often fail to generalize
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sustainable fluorination reactions. Under the supervision of Dr. Chris Ewels, a CNRS Research Director and expert in DFT modeling of nanocarbon materials, the postdoc will lead Work Package 2 (WP2), which aims
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LMPS - CNRS - CentraleSupélec - ENS Paris-Saclay | Gif sur Yvette, le de France | France | 5 days ago
on their operational history. This knowledge is fundamental for the adaptation of future maintenance and replacement policies. It will indeed make it possible to better manage the renewal of the network by making
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. The core objective is to bridge model-based and learning-based approaches by embedding biomechanical knowledge into data-driven models to achieve robust, physically consistent, and context-aware control
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synthesizing findings with prior knowledge from the scientific literature, a process that today depends heavily on manual expert interpretation. Recent advances in large language models, agentic systems, and
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SEVERUS in silico modeling, with emphasis on performance, scalability, and reproducibility. Activities include engineering modular workflows in NEST (and ARBOR, if needed), profiling and optimizing
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different model sizes and deployment settings. Apply and advance model compression techniques, including quantization, pruning, knowledge distillation, low-rank adaptation, and related methods. Conduct
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publications, participating in conferences). Required skills: • Solid knowledge of heterogeneous catalysis, including the synthesis, physicochemical characterisation and catalytic evaluation of composite
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of Biostatistics at Brown University is seeking a highly motivated individual for a postdoctoral research associate position interested in developing statistical methods for modeling medical imaging data
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can be found at: https://www.kcl.ac.uk/mathematics About the role Applications are invited for a Lectureship in Applied Mathematics with a focus on quantitative modelling in the Department