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chain network analysis and geospatial modeling. The successful candidate will have strong data science skills, including experience working with large, complex data from varied sources, and machine
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particular, the postdoc will focus on applying reinforcement learning to discover vulnerabilities and failure modes in software systems that support critical infrastructure, in particular AI-based decision
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EGFRvIII can enhance survival. Work will also be done to define how PCPS enhances specific components of the immune response utilizing single cell sequencing for the TCR and transcriptome on the CD8+ T cells
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the development of natural and built urban systems and human-system collaborations. Successful candidates will be expected to define an independent research agenda and to work closely with Stanford University
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markets computationally tractable approaches to school redistricting with choice aggregating community feedback on resource allocation policies. Projects will be defined and scoped by the postdoc
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increases Tackling climate change is a defining challenge of the 21st century. The transition to a low-carbon energy system will solve about three-fourths of the climate problem. At the same time, the new
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) signaling. The Huttenhain lab integrates cutting-edge MS-based proteomics, functional genomics, imaging, and other molecular biology techniques to profile the spatiotemporal nature of GPCR signaling networks
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operator faces will change daily, but not drastically: although demand will vary, the network structure will remain largely stable. Thus, there is likely underlying structure linking the problems that arise
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skills in statistical software (e.g. R, Stata, Python) and working knowledge in SQL Excellent written and oral communication skills Strong record of distinguished scholarly achievement, including written
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use of cutting-edge informatics to prioritize causal variants for validation using functional genomics, including CRISPR. The overall goals of this work are to define novel disease targets and context