-
efficiency and accuracy in link-tracing designs (e.g. Respondent driven sampling) Partial graph data collection strategies for networks (e.g. Aggregated Relational Data) Large scale models for anomaly
-
such as fluorescence lifetime imaging microscopy, optical sensors, light-activated actuators, electrophysiology, molecular biology, quantitative rodent behavior, and computational approaches. We aim
-
maintaining large, international collaborative scientific networks. The ideal candidate is familiar with the SSPs and RCPs and their application in integrated assessment modeling; have experience in developing
-
biology, post-translational modifications, chemical biology, and proteomics. Develops proficiency in career skills, including writing, public speaking, networking, and critical evaluation of scientific
-
have access to multiple datasets with cognitive and clinical assessments and fluid and imaging biomarkers. Our cohorts include the Dominantly Inherited Alzheimer Network (DIAN; our longitudinal study of
-
. Develops proficiency in technical skills with particular focus on longitudinal analysis. Develops proficiency in their ancillary skills, e.g., writing, public speaking, networking, critical evaluation
-
response biology. Develops proficiency in career skills, including writing, public speaking, networking, and critical evaluation of scientific literature. Presents scientific work both inside and outside
-
science, and applied math communities through attendance at conferences, workshops, and networking events. They will receive hands-on research mentorship and professional development support, with potential
-
be for self-directed research including publications, dissertation, and developing an independent research agenda. The Quality Evidence for Health System Transformation (QuEST) Network is an initiative