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: The Pain Intelligence Lab The Stanford Center for Population Health Sciences Interdisciplinary collaborations within Stanford School of Medicine Opportunities to engage with national networks in rheumatology
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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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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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algorithmic performance. For instance, the scheduling problems that an electric grid operator faces will change daily, but not drastically: although demand will vary, the network structure will remain largely
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of the selected candidate, budget availability, and internal equity. Pay Range: $73,800-$80,000 The LEarning VAriability NeTwork Exchange (LEVANTE) project seeks a Postdoctoral Scholar to study psychometrics and
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. At single cell level, how does the same genome give rise to thousands of different cellular phenotypes in the brain? 2. At the tissue level, how do gene networks orchestrate intercellular communication
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and other machine learning models (especially neural network models, time-series models) and coding in python and R. Strong collaborative skills and ability to work well in a complex, multidisciplinary
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outreach to other school districts in the lab’s network interested in taking a socio-technical approach to assigning educational resources. Candidates will be evaluated according to their: Scientific record
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you would be a great fit for the Stanford Energy Postdoctoral Fellowship. How will you leverage the training, network, resources, and support of this fellowship program to impact the energy field? What
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uniquely cross‑disciplinary team and work closely a network of collaborators. • Jan Zimmermann — University of Minnesota • Aaron Batista — University of Pittsburgh • Kimberly Stachenfeld — Columbia