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Field
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uses a range of approaches, including in vivo and ex vivo mouse models, primary human cell culture, and in vitro organoid cultures. Responsibilities Responsibilities include conceptualizing and
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, various cutting-edge experimental and computational approaches in the areas of functional genomics, cell biology, biochemistry, single-cell/spatial multi-omics, data mining, drug screening, and disease
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responses and protective efficacy of vaccines in laboratory animal models (e.g., guinea pigs and mice) Mammalian cell and virus cultivations Bacterial and viral gene cloning and manipulation Lab animal
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evaluate experimental guinea pig and mouse models of viral infection and placental/fetal development Collection and analysis of experimental animal’s organs and tissues Bacterial and viral cultivations
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. ● Experience with mouse models. ● Experience with cell and molecular biology techniques including PCR, western blotting, flow cytometry, cell culture and immunohistochemistry assays. Position Summary
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the possibility of yearly renewal subject to funding availability. Responsibilities • Design and implement deep learning architectures, AI agent pipelines, and computer vision algorithms to achieve project goals
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models to simulate lifeless and inhabited worlds, and Developing disequilibrium-, redox-, and information-based metrics to understand and quantify the influence of life on planetary environments
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Massachusetts Institute of Technology (MIT) | Cambridge, Massachusetts | United States | about 2 months ago
: PhD in nuclear engineering, applied physics, computational science, or a closely related field; demonstrated experience in Multiphysics modelling, numerical methods for PDEs, and code verification and
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in AI-modeling, Monte Carlo simulation, and coding. The successful candidate will work alongside a multidisciplinary team, leveraging artificial intelligence and computational methodologies to optimize
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jurisdictions utilizing land use-value assessment estimates. Duties include, but are not limited to: development of computational methods, maintenance of current models and data sets, identifying and testing