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Field
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learning (ML) to address future physics and detector challenges. Current physics interests include Standard Model measurements and searches for new phenomena. We welcome applicants who are excited
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Are you interested in the empirical foundations of flood damage modelling and keen to translate that knowledge into practical strategies for insurers to reduce losses through early warning and
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Potentials (MLIP), machine learning (ML) predictive models and AI tools. Activities : Computer science implying ML and AI tools applied to material science Where to apply Website https://umontpellier.nous
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hope for cancer patients and their families and play a critical role in strengthening the fabric of our communities by gaining and protecting their trust and providing access to the outstanding oncology
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biological approaches, in vitro cell culture systems, and novel mouse models. Optimal candidates will have experience with immunometabolism and use of these techniques and models. The overall goal is to
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of agentic AI systems for accelerating computational catalysis and experimental design. The successful candidate will contribute to building AI-native frameworks that combine physics-based modeling, machine
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stimulation, laryngeal dysfunction, and implantable neural devices, as well as developing their own ideas for new projects. Efforts will focus on working with pre-clinical models which facilitate translating
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aspects of data collection, dataset preparation, software implementation, model validation, laboratory maintenance, cyberinfrastructure development, and documentation, depending on the role. Conduct
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on musculoskeletal biology. The qualified candidate will oversee larger research projects. Requirements: The candidate will do Experimental training in preclinical surgical mouse models or clinical research is
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Yale School of Medicine - Department of Genetics | New Haven, Connecticut | United States | about 2 months ago
lineage-tracing mouse models, lung injury and tumor-initiation systems, single-nucleus multiome (RNA and ATAC) and spatial profiling, and validation in human early-stage lung adenocarcinoma specimens