Bioinformatics Research Analyst


Washington University School of Medicine - Neurogenomics and Informatics Center


St. Louis, Missouri

Principal Investigator

Laura Ibanez


Candidates can apply by navigating to and searching for the job opening number (49023)


The NeuroGenetics and Informatics (NGI) center at Washington University School of Medicine is recruiting a bioinformatics research analyst to work in Dr. Ibanez's group at the Washington University School of Medicine. The NGI generates and analyzes high-throughput multidimensional omic data to study neurodegeneration and diseases of the central nervous system, with emphasis on Alzheimer’s disease, Parkinson’s disease, and other dementias. The goal of Dr. Ibanez's research is to use omic approaches to generate biomarkers for Alzheimer’s Disease, Parkinson Disease and other neurodegenerative disease.

Her lab is focused on the generation of minimally invasive tools to predict neurodegenerative diseases and monitor progression and response to treatment using RNA-Seq data and machine-learning algorithms.

The center is looking for a bioinformatics research analyst with expertise in RNA-Seq data analyses and machine learning to work in different projects that focus on the identification of genes dysregulated in Alzheimer's and Parkinson’s disease that can be used as biomarkers.

She/he will join a multidisciplinary team of computational and statistical researchers working in bioinformatics, statistical genomics, and genetics. The team comprises more than 20 people dedicated to understanding the architecture of neurodegenerative diseases.


Essential Functions:

1. To write and optimize analyses pipelines (scripts) for RNA-Seq.

2. Analyze data including QC, and organize the data properly.

3. Perform statistical analyses.

4. Create reports of the analyses.


The candidate will hold a master in statistics, bioinformatics, computational biology, biostatistics, statistical genetics, medical statistics, mathematics or similar. The candidate should have a strong background in RNA-Seq analyses (STAR, SALMON, DESEQ2) and machine learning. Working knowledge of UNIX, Perl/Python, R and Docker are also required.