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Research Centre (CRC) 1450 “inSight – Multiscale imaging of organ-specific inflammation” (https://www.uni-muenster.de/CRC-inSight) The project is based in the research group of Prof. Dr. Kerstin Steinbrink
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Inria, the French national research institute for the digital sciences | Villers les Nancy, Lorraine | France | 19 days ago
required to evaluate and train learning models contributing to robot software (dashboard, automated functions, etc.) depending on the profile, contributing to the design of physical interfaces with humanoid
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to staff position within a Research Infrastructure? No Offer Description The CCARBON Atmosphere module is dedicated to developing and applying process-based models for major Brazilian agricultural
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Description Context Federated learning (FL) enables models to learn from distributed datasets across diverse clients (e.g., edge devices, hospitals, or industrial sites) while maintaining privacy [1]. A major
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investigate HIV-induced vascular dysfunction and neuroAIDS molecular mechanisms using in vitro and in vivo (animal models) approaches. Specifically, the person will utilize HIV mouse models and HIV-1 infected
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. Manages and is responsible for organizational development, curriculum development and delivery, project management, project leadership, change management, business process modeling, process improvement
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at Cornell University is seeking a Postdoctoral Associate to advance research on maize and grass molecular diversity using genomic large language models (AI). The goal is to design nitrogen-efficient maize
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institutional support services, is reminiscent of the Oxford-Cambridge model. The undergraduate colleges include Pomona College, Scripps College, Claremont McKenna College, Harvey Mudd College, and Pitzer College
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- research experience in the evaluation of global wave reanalysis and integration of topographic and bathymetric datasets, as well as experience in the implementation of XBeach and SWaN models. Preferential
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modelling. MISSION You will actively contribute to the development and evaluation of new hybrid computational method to predict biological tissue deformation with subject-specific material properties