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-based role based at Stanford University’s Environmental Measurements Laboratory May require ~20% travel to train others on analytical approaches and learn new approaches at other laboratories (domestic
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fellowships and NSF SBE postdoctoral awards. We especially welcome applicants with theoretical interest in child language development, strong computational and analytical skills (deep learning frameworks), and
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novel, tablet-based assessments of young learners’ curiosity, creativity, initiative, problem-solving, and scientific inquiry, which are skills that create a strong foundation for lifelong learning
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advanced analytics to develop novel approaches that improve patient outcomes and expand access to life-saving surgical interventions. The fellowship includes opportunities for mentorship, professional
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in the U.S. There will also be extensive opportunities to learn more about and work with Census-held administrative records. The successful candidate will have strong data science skills, including
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research-practice partnerships and collaborations with community organizations. These partnerships provide fellows with opportunities to learn to collaborate with practitioners and policymakers to identify
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and patient-reported outcomes; (b) observational research and comparative effectiveness studies; (c) intervention studies; (d) clinical informatics, mobile/electronic health; (e) machine learning
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and aggression, using optogenetics, in vivo imaging, electrophysiology, and sophisticated machine learning/artificial intelligence analyses of mouse behavior. All projects have translational components
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, and MRV performance) and identify optimal deployment models coupled with learnings from forest management. Conduct techno-economic and life-cycle assessments (TEA/LCA) integrating forest operations