105 modelling-and-simulation-of-combustion-postdoc Postdoctoral positions at University of Washington
Sort by
Refine Your Search
-
& Responsibilities: Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2/ . Trains under the supervision of a faculty mentor including (but not limited
-
, to define novel biomarkers, and to identify novel therapeutical targets. We have pioneered in the integration of genetics with omic data to identify proteomic signatures and develop novel predictive models
-
at major conferences and in peer-reviewed journals, postdocs are encouraged and mentored in writing grant proposals. A notable feature of APL postdoc positions is the ability to submit grant proposals as PIs
-
variants in inborn errors of immunity. Job Description Primary Duties & Responsibilities: Information on being a postdoc at WashU in St. Louis can be found at https://postdoc.wustl.edu/prospective-postdocs-2
-
involve sensor design, including analog front-end design, light source modulation, sensor miniaturization including PCB design, sensor testing via physiology-mimicking phantoms, animal models, healthy
-
other disease models that are valuable in studying the etiology and treatment for these devastating diseases. We combine in vivo, ex vivo, and in vitro methods to study the pathogenic mechanisms in a
-
, single-cell multiomics, tissue engineering, and animal models. Our current research primarily focuses on four key areas: 1) Developing robust, chemically defined differentiation protocols to generate
-
scholar will be expected to be involved in research efforts in at least one of the following: transportation data analytics, highway safety, transportation equity and sustainability, traffic simulation
-
neuropathological severity. The Postdoctoral Research Associate will be mentored by Dr. Carlos Cruchaga and will focus on the identification and modification of circRNAs in in vitro models of Neurodegenerative
-
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 detection on graphs