Institution/Company:

Washinton University in St. Louis

Location:

St. Louis

, Missouri

 United States

Job Type:

Staff

Degree Level Required:

PhD

163 days ago Apply now

Description:

The NeuroGenomics and Informatics (NGI) Center lead by Dr. Carlos Cruchaga at Washington University School of Medicine is recruiting a Bioinformatics Scientist to work on Genome-Wide Association Studies. We are seeking an experienced, self-motivated, self-driven scientist to work as a part of vibrant group in a fast-paced environment. The NGI generates and analyzes Whole-Genome and high-throughput multi-dimensional omic data to study neurodegenerative diseases of the central nervous system with emphasis on Alzheimer’s and Parkinson’s disease. The goal of our research is to use genomic and multi-omic approaches to understand the biology of Alzheimer’s and Parkinson diseases. Our labs have pioneered the use of new biomarkers as endophenotypes for genetic studies.

Responsibilities:

  • Primary duties
  • Independently develop a wide variety of computer programs to meet the needs of data collection, quality control, analysis and report generation
  • Perform complex data analysis and writes interpretative reports
  • Collaborate within cross-functional teams
  • Provide analytical support for internal projects and external collaborations
  • Improve and supervise database structure: includes updating, validating, curating and harmonizing longitudinal, cross-sectional data from different sources
  • Provide a centralized, confidential and secure access to phenotypic data to Principal investigators
  • Respond to data queries from Principal Investigators and external collaborators

Qualifications:

  • Ph.D. degree in Neurogenetics, Bioinformatics, Computational Biology, Statistical Genetics, Biostatistics, Medical Statistics, Neuroscience, Genetics, Statistics, Mathematics or related.
  • At least two years of experience working in genomics with large datasets, preferably in a research environment
  • Strong background in PLINK, QC, IBD, PCA; R, bash and excel (Python, Perl, SAS, SQL, Docker are a plus) or other analyses toolset.
  • Knowledge of association analyses, PRSice, MAGENTA, Mendelian Randomization, MANTRA, Coloc, QTL and Unix/Linux
  • Excellent communication and problem solving skills
  • Familiar working in cross-functional teams
  • Good understanding of computational biology and flexibility to work within a large dynamic scientific team

Additional Information:

How to Apply

Interested candidates please send cover letter and resume to Oscar Diaz Ruiz, Ph.D., Program Manager. ( doscar_at_wustl.edu )

Keywords:

Analysis

Biostatistics

Clinical

Epigenetic

Genome-wide

Genomics

Machine Learning

Mathematics

Models

NGS

Phenotyping

Programming

Quantitative

RNA

Posted on: