Bioinformatics Research Analyst – Genetics

Washington University in St. Louis

St. Louis (MO)

On-site

USD 42,000 - 76,000

Full time

14 days+

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Benefits offered by this job

Vacation & holidays
Health insurance
Metro transit U-Pass
Tuition assistance
Caregiver leave

Job summary

Washington University in St. Louis is seeking a Researcher for the Dougherty Lab to lead analysis and interpretation of extensive transcriptomic datasets in psychiatric genetics. You will develop and apply computational methods, mentor lab members, and present research findings.

The role emphasizes dry-lab and wet-lab integration, training in genomics analyses, and collaboration with in-house and external teams. Strong programming and communication skills are essential.

Qualifications

  • Bachelor's degree required or equivalent experience.
  • Experience with genomics data analysis and statistical methods.
  • Strong programming skills in R and/or Python.
  • Experience with HPC and Linux environments.
  • Ability to communicate results clearly and work in a team.

Responsibilities

  • Implements algorithms for omics data analysis.
  • Visualizes results from diverse experiments.
  • Manages data storage/analysis pipelines for large datasets.
  • Coordinates project work with investigators and institutions.
  • Participates in hypothesis development and experimental design.
  • Develops software to assist data collection and teaches concepts to lab members.
  • Provides guidance and troubleshooting for software use.
  • Assists with reporting methods and results.

Skills

R and/or Python
Statistical analysis
Data visualization
Computational biology
Team collaboration

Education

Bachelor's degree
Bachelor's or Master's in bioinformatics/genomics/data science

Tools

Nextflow
Snakemake
SLURM/LSF HPC
Docker/Singularity
Git/GitHub
Conda
RNA-seq tools (DESeq2/EdgeR/limma)
Seurat/scanpy

Job description

Job Title

Researcher for Dougherty Lab

Location

Saint Louis, MO 63110

Position Summary

The Dougherty lab is a mixed wet-lab dry lab environment studying gene expression in the brain in the context of psychiatric genetics. We are generating extensive transcriptomic datasets and need a creative, motivated and intelligent researcher to take the lead in the analysis and interpretation of this data. We have an extremely strong record in gene expression profiling analysis and can offer mentoring in the analysis of genomics experiments and the use of computational statistics. Provides critically complex dry-lab research and experimentation for the team, allowing the advancement of scientific analysis and discovery. The role will further serve as a subject matter expert offering support, training and guidance relative to the discipline/area. They may also participate and/or present on the research developed, or the established work of those within the department, especially to team meetings.

Job Description
Primary Duties & Responsibilities
  • Implements algorithms and computer software for analyzing omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical].
  • Visualizes results from a wide range of different experiments
  • Data management and analysis solutions that aid in the storage, investigation and dissemination of large data sets.
  • Coordinates research project with other investigators and institutions.
  • Participates in developing hypotheses and experimental design.
  • Creates software to assist in data collection, and teaches basic or novel elements of computer science to others in the lab
  • Provides guidance and troubleshooting support for the use of software.
  • Assists with reporting of methods, data and results.
Working Conditions: Job Location/Working Conditions
  • Works in a laboratory environment with potential exposure to biological and chemical hazards
  • Must be physically able to wear protective equipment and to provide standard care to research animals
  • Normal office environment.
Physical Effort
  • Typically sitting at desk or table.
  • Repetitive wrist, hand or finger movement (PC Typing).
Equipment
  • Office equipment.
Required Qualifications
  • Education: Bachelor's degree or combination of education and/or experience may substitute for minimum education.
  • Certifications /Professional Licenses : No specific certification/professional license is required for this position.
  • Work Experience: Relevant Experience (2 Years)
  • Skills: Not Applicable
  • Driver's License: A driver's license is not required for this position.
Preferred Qualifications
  • Bachelor's or Master's degree in bioinformatics, genetics, statistics, data science, computer science or a related field.
  • Enjoy contributing as a team member in a fast-paced interactive environment, as well as working on self-directed research within the broader goals of the group.
  • Excellent computational skills. The ideal applicant will be well-versed in R and/or Python, with experience in a compiled language (e.g., C) as a plus.
  • Demonstrate effective oral and written communication and proven ability to work in a collaborative environment.
  • Background in the application of statistical methods in the biological and medical sciences is advantageous.
  • Experience with automated analysis pipeline frameworks such as nextflow or snakemake.
  • Experience navigating in a Linux/UNIX environment, and job scheduling (SLURM, LSF) with high-performance computing (HPC) clusters
  • Experience teaching or mentoring in computer science or bioinformatics
  • Experience with containerization software such as singularity, apptainer, docker, and conda
  • Experience using version control (e.g., git and GitHub)
  • Experience with large datasets and data transfers (e.g., Globus, sftp)
  • Familiarity with popular RNA-seq analysis packages (e.g., DESeq2, EdgeR, limma) and single cell RNA-seq packages (e.g., Seurat, scanpy)
  • Familiarity with basics and application of machine learning (e.g., linear regression, PCA)
  • Some experience in data generation or wet-lab background is a plus.
  • Good understanding of computational biology.
  • Ability to analyze and interpret large complex data sets, such as genome sequencing, RNA-seq gene expression studies, human genetic studies, and model organism studies, and to communicate data in a clear, concise manner.
  • Expertise in standard bioinformatics tools.
  • Ability to balance multiple projects.
Salary Range

$41,700.00 – $75,600.00 / Annually The salary range reflects base salaries paid for positions in a given job grade across the University. Individual rates within the range will be determined by factors including one's qualifications and performance, equity with others in the department, market rates for positions within the same grade and department budget.

Benefits Statement
Personal
  • Up to 22 days of vacation, 10 recognized holidays, and sick time.
  • Competitive health insurance packages with priority appointments and lower copays/coinsurance.
  • Take advantage of our free Metro transit U-Pass for eligible employees.
  • WashU provides eligible employees with a defined contribution (403(b)) Retirement Savings Plan, which combines employee contributions and university contributions starting at 7%.
Wellness
  • Wellness challenges, annual health screenings, mental health resources, mindfulness programs and courses, employee assistance program (EAP), financial resources, access to dietitians, and more!
Family
  • We offer 4 weeks of caregiver leave to bond with your new child. Family care resources are also available for your continued childcare needs. Need adult care? We've got you covered.
  • WashU covers the cost of tuition for you and your family, including dependent undergraduate-level college tuition up to 100% at WashU and 40% elsewhere after seven years with us.
EEO Statement

Washington University in St. Louis is committed to the principles and practices of equal employment opportunity. It is the University's policy to provide equal opportunity and access to persons in all job titles without regard to race, ethnicity or shared ancestry, color, national origin, citizenship (where prohibited by federal law), age, religion, sex, sexual orientation, gender identity or expression, disability, protected veteran status, or genetic information. As a federal contractor, the university maintains affirmative action programs to implement its equal employment opportunity policy for individuals with disabilities and protected veterans, in accordance with Section 503 of the Rehabilitation Act of 1973, as amended, and the Vietnam Era Veterans' Readjustment Assistance Act of 1974 (VEVRAA), as amended.

Tagged as: Life Sciences
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