67 parallel-computing-numerical-methods-"Simons-Foundation" Postdoctoral positions at Stanford University
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funded by the Simons Foundation that aims to uncover how opportunities for action ("affordances") shape neural representations, perception, and behavior. Why this position? You will sit at the center of a
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disease. Key responsibilities include: (1) Conduct computational methods development and analysis for systems-level understanding of host-immune responses to diseases. (2) Collaborate effectively with a
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analysis of multiple disease-specific datasets and contribute to the development of novel methodologies in this space. The ideal applicant will have a strong background in bioinformatics methods and a keen
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therapeutics. We are seeking a highly motivated, collaborative, and independent Postdoctoral Researcher to spearhead a research program within the general areas of protein biochemistry, engineering, and
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are seeking a highly motivated, collaborative, and independent Postdoctoral Researcher to spearhead a research program within the general areas of synthetic genomics and synthetic biology, as
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position to join NIH-funded projects in collaboration with the U.S. Census Bureau's Enhancing Health Data (EHealth) Program that develop new integrated data to improve our understanding of the socio-economic
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an interest in applying health services research and policy methods to real-world questions in acute and population health. Key Responsibilities Conduct and manage research projects focused
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multidisciplinary team studying the genomics of neurodegenerative diseases, with a special focus on Alzheimer’s Disease (AD). Current research focuses on using novel methods to detect genetic associations with
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community that spans discovery to clinical implementation. Specific Responsibilities include: experimental design, data acquisition, data processing, statistical computation, methods development, data
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assessment of lymphatic flow, 2) Advancing methods for contrast-enhanced MRL, 3) Creating ideal contrast agents for MRL, and 4) generating phantom and animal models for MRL optimization and validation