32 phd-position-in-data-modeling Postdoctoral positions at Stanford University in United States
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model fairness and model generalizability across multi-institutional electronic health records databases. The researcher will have access to the real-world EHR data from almost 20 sites across
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and pain research Required Qualifications: PhD (or equivalent) in epidemiology, health data science, biomedical informatics, biostatistics, public health, or a related field. Demonstrated experience
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position will require establishing new model species in the lab, developing protocols for experiments that have not been attempted before, and collaborating with an international and interdisciplinary team
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applications for a postdoctoral fellowship position to join a project investigating trafficking risks in charcoal supply chains in Brazil. The position is open to recent graduates of PhD programs in statistics
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. Qualifications for this position include a PhD in Computer Science, Artificial Intelligence, Natural Language Processing, Human-Computer Interaction, or a closely related field. Candidates should have demonstrated
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, this position offers access to some of the most detailed clinical data available — including second-by-second EHR metadata and continuous physiologic monitoring — to study how care actually happens and how it can
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Postdoc Fellowship - Vitercik” Does this position pay above the required minimum?: Yes. The expected base pay range for this position is listed in Pay Range field. The pay offered to the selected candidate
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-cigarette nicotine vapor, augment model AAA. Exposure to tobacco smoke, nicotine, and vaping can cause cellular epigenetic alterations, which may be transmitted in a transgenerational fashion. Our data show
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) . Lab information can be found here: http://profiles.stanford.edu/nathan-lo (link is external) . Review of applications will be performed on a rolling basis and continue until the position is filled. Does
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. Leading the analysis of single-cell and spatial transcriptomics data. Applying and developing the analysis framework for spatiotemporal modeling. Publication in top-tier journals, and apply and obtain