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checks with advanced machine learning architectures, specifically Long Short-Term Memory (LSTM) networks and Variational Autoencoders (VAEs). The researcher will use historical QC archives dating back
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lab position (though has dry lab components!) involving the use of mouse models in an animal BSL3 facility. Previous BSL3 experience is not a requirement. Candidates with experience with mice, flow
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lung fibrosis. The ideal candidate will independently perform studies utilizing established in vitro, ex vivo and in vivo preclinical models and will have the opportunity to develop and refine novel
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regulatory decision-making around the implementation of these technologies. A key component of the work will involve developing an ex-ante economic model to identify cost-effective strategies for implementing
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Framework for Medical Device Surveillance https://reporter.nih.gov/project-details/11091149 · CardioOnco-AI: AI-Empowered Cardiotoxicity Risk Prediction Among Breast Cancer Survivors Using Multi-Site
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. The main role is to support in vivo studies of the effects of gene therapies in preclinical mouse models. This includes animal husbandry, colony management, drug treatments, behavioural assays, genotyping
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protein expression and purification, biochemical screening assay development, computational structural modeling, cell-based antiviral validation studies, and exposure to preclinical small-animal research
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an understanding of large language models or conversational AI frameworks (e.g., OpenAI API, Gemini AI). You have experience setting up and maintaining databases (e.g. SQLite, MySQL). You have an
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contribute to the development and validation of computationally efficient motor-twin models for permanent magnet synchronous machines. The work will focus on machine modelling, parameter and state estimation
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members have won Nobel Prizes for these ideas - the first business school to achieve this accomplishment. For more information about the University of Chicago Booth School of Business, please visit: http