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. In complementary studies, we are investigating antigen-specific responses and mucosal tolerance using multiple different in vivo and in vitro models and human samples. Candidates with backgrounds in
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mainly be connected to DRIVE PR, but may also be linked to related projects within data-driven product realisation, digital engineering, systems engineering, geometry assurance, automation, or model-based
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research and implementation. You will also develop novel algorithms using state-of-the-art computer vision and machine learning techniques (segmentation, multimodal AI, foundation models, agentic frameworks
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to post-process characterization. This environment enables the creation of high-fidelity digital twins and AI-ready datasets that support real-time monitoring, predictive modeling, and process optimization
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organoids. Candidate FDA approved drugs will be tested using organoid systems and animal models of infection. The initial focus will be on RVFV, but may be extended to other emerging viruses. The research
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, Interoperable) principles Build and extend tools that validate datasets, and check whether they meet AI-readiness requirements. Help automate dataset preparation using reporting format templates and structured
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PET resins and develop simple models through conventional statistical analysis methods to be able to screen PCR PET resin material to enable its use in industrial packaging applications. In
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models, host–pathogen interactions, and molecular and cellular immunology. Experience with immunological techniques such as flow cytometry, cytokine analysis, multiplex immunoassays, ELISA
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analytical and modeling approaches to interpret experimental results. Collaborate with internal and external research teams to define and advance research directions. Present research findings and publish
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that include mid-circuit measurements and feedforward Quantum simulation of many-body and lattice-gauge theory models Microscopic physics of Josephson junctions Other topics of mutual interest About the Yale