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Postdoctoral position in AI for protein design with applications to TCR & BCR models The lab of Prof. María Rodríguez Martínez at the Department of Biomedical Informatics & Data Science, Yale School
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applications in python with PyTorch/Huggingface/SpaCy, applications of computer vision and signal processing in Tensorflow or PyTorch, Llama and GPT models. Essential Duties Develop and execute new and/or highly
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. Studies incorporate approaches in both primary human immune cells and in vivo mouse intestinal model systems. Education and experience: Candidates must have a PhD or equivalent degree with a strong
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a particular focus on cytokine-based drugs, using immune competent murine models and human cell culture systems for early drug development. We also study mechanisms and determinants of immune related
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the Digital Atlas, this project will be highly resolved in space and take novel approaches to modeling uncertainty. It will use and potentially expand a large collection of data compiled by Fabian Drixler and
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animal models, preclinical and clinical PET imaging, image analysis, kinetic modeling, data analysis, and results dissemination. Qualifications: The ideal candidate will have some prior hands-on experience
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models, and blockchain-based privacy-preserving learning. The focus will be blockchain technology and machine learning, and candidates with at least one of the backgrounds are welcomed to apply
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/CT and PET/MR imaging for cardiac applications. Responsibilities involve working with preclinical large animal models, preclinical and clinical PET imaging, image analysis, kinetic modeling, data
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postdoctoral position at the interface of decision analytic modeling, pharmacoepidemiology and clinical hematology-oncology within the Section of Medical Oncology and Hematology, Department of Internal Medicine
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the cell intrinsic immune machinery and DNA damage and repair processes using in vitro cell models, genetic screens (such as CRISPR and RNA interference), and animal models. We have a strong translational