Postdoctoral Research Associate (rna Transcriptomics In Alzheimer's Disease) - Psychiatry
Washington University in St. Louis
St. Louis, Missouri, US
Base pyy is commensurate with experience
On-site
Rna-seq data analysis
Circrna identification
Computational and statistical analyses
Washington University in St. Louis is seeking a Postdoctoral Research Associate to analyze RNA-seq data related to circRNAs and neurodegenerative diseases, particularly Alzheimer’s. The successful candidate will engage in a collaborative research environment to uncover novel biomarkers and therapeutic targets
Job Summary
We are hiring a postdoc to work with RNA-seq data in order to identify circRNA implicated in complex traits including Alzheimer’s disease, Parkinson’s disease and stroke using novel and integrative computational and statistical analyses.
We have generated brain and blood transcriptomic data in thousands of samples with several neurodegenerative diseases with emphasis on Alzheimer’s disease, Parkinson’s disease, and other dementias with the goal of understanding the biology of these diseases, to define novel biomarkers, and to identify novel therapeutical targets.
The candidate will hold a PhD in Statistics, Bioinformatics, Computational Biology, Biostatistics, Statistical Genetics, Medical Statistics, Mathematics or similar.
Matching Summary
Match Score: 85
Washington University in St. Louis is seeking a Postdoctoral Research Associate to analyze RNA-seq data related to circRNAs and neurodegenerative diseases, particularly Alzheimer’s. The successful candidate will engage in a collaborative research environment to uncover novel biomarkers and therapeutic targets.
Salary
Base pay is commensurate with experience
Skills & Requirements
Must-have
RNA-seq data analysis
circRNA identification
computational and statistical analyses
second-generation sequencing analyses
Nice-to-have
multidisciplinary and collaborative environment
novel therapeutical targets
novel biomarkers
Key Requirements
PhD in Statistics, Bioinformatics, Computational Biology, Biostatistics, Statistical Genetics, Medical Statistics, Mathematics or similar
Strong background in second-generation sequencing analyses (RNA) with focus on circRNAs, pathways analyses and biomarker discovery