20 postdoc-applied-linguistics Postdoctoral positions at University of Nebraska Medical Center
-
. Prepare technical reports for internal use and funding agencies. MBHL (https://ww w.un mc.edu/mbhl/) is an interdisciplinary group of researchers who are committed to CTR aimed at improving patient health
-
position in big data analysis, substance use, neurocognition, and tobacco regulatory science. The position entails research on (1) analysis of big data using advanced statistical methods, (2) assessment
-
Developmental and Degenerative Neuroscience in the Department of Neurological Sciences provides a vibrant research community with access to world- class facilities. For consideration and to apply
-
position in big data analysis, substance use, neurocognition, and tobacco regulatory science. The position entails research on (1) analysis of big data using advanced statistical methods, (2) assessment
-
project funds are secured and from a non-federal source. The position involves applying bioinformatic and statistical tools to existing multidimensional datasets, including metagenomic, transcriptomic
-
. Applicants must have a PhD degree with an emphasis in biochemistry, neonatology, biology or related field. This individual will conduct bench and translational cardiovascular research that will utilize in
-
to complete their degree within the next six months are also encouraged to apply.) Strong publication record. Experience with rodent models, cardiovascular cell biology, or bioinformatics is highly desirable
-
groundbreaking contributions to the field of neurobiology. If you are ready to take on this exciting challenge and make a significant impact in the field, we encourage you to apply. Join us in our mission
-
. This individual will conduct bench and translational cardiovascular research that will utilize in vitro and in vivo models of congenital heart defects. This individual will complete projects that require expertise
-
a non-federal source. The position involves applying bioinformatic and statistical tools to existing multidimensional datasets, including metagenomic, transcriptomic, proteomic, and metabolomic