Bioinformaticist - Neurology

Location: Saint Louis, MO 63110 | Scheduled Hours: 40

About the role

The Orr Lab is seeking support for computational and quantitative research focused on aging, neurodegeneration, and human disease. The successful candidate will work closely with bioinformatics scientists, experimental researchers, and collaborators to analyze, integrate, and interpret complex high-dimensional molecular datasets. This position will support projects spanning multiple omics technologies, including spatial proteomics and transcriptomics, bulk transcriptomics, single-cell and single-nucleus RNA sequencing, proteomics, epigenomics, and whole-exome/genomic sequencing.

A major focus of the position will be the development and application of statistically rigorous, reproducible, and scalable computational workflows. The ideal candidate will understand not only how to use established bioinformatics tools, but also how to select appropriate analytical approaches based on the experimental design, structure of the data, and biological question. The individual will work in a highly collaborative research environment and will contribute analytical results to manuscripts, abstracts, presentations, grant applications, and ongoing research discussions.

Responsibilities

• Designs, develops, and implements algorithms and computer software for omics-based data sets (high-throughput, massively parallel genomic/proteomic/clinical).
• Develops data management and analysis solutions that aid in the storage, investigation, and dissemination of large data sets.
• Leads independent research projects, including design of research protocols and development of procedures for the collection, verification, and management of data.
• Creates clear, informative, and publication-quality data visualizations, including heatmaps, dimensionality-reduction plots, statistical summaries, pathway/network visualizations, and other figures appropriate for scientific communication.
• Performs data quality control, preprocessing, normalization, filtering, identifying technical artifacts, outliers, batch effects, and other sources of unwanted variation.
• Performs comprehensive analysis of high-dimensional omics datasets, including:
  • Spatial transcriptomic and spatial proteomic datasets
  • Bulk RNA sequencing
  • Single-cell and single-nucleus RNA sequencing
  • Proteomic datasets
  • Epigenomic datasets
  • Whole-exome and genomic sequencing data
• Analyzes single-cell and single-nucleus sequencing datasets, including:
  • Cell- and sample-level quality control
  • Normalization and feature selection
  • Dimensionality reduction
  • Clustering
  • Cell-type annotation
  • Differential expression
  • Pseudobulk analysis
  • Cell-composition and differential-abundance analysis
  • Pathway, gene set enrichment, and functional/network analysis
  • Integration across samples, batches, conditions, or datasets
• Evaluates commercial and academic bioinformatics software.
• Works closely with wet-lab scientists, neuropathologists, statisticians, computational researchers, and external collaborators to translate biological questions into appropriate computational analyses.
• Trains other researchers on the everyday use of analysis software and research databases.
• Assists with grant preparation and reporting of methods, data, and results.
• Solves practical problems relating to difficulties with equipment or test subjects; suggests technical or procedural improvements in testing methods.

Requirements

• Bachelor’s degree.
• 4 years of research experience.

Skills

• Proficiency in R.
• Experience analyzing at least one major class of high-throughput molecular data, such as spatial omics, transcriptomic, single-cell, proteomic, epigenomic, or genomic.
• Familiarity with the Bioconductor ecosystem and commonly used bioinformatics frameworks.
• Experience with packages or analytical frameworks such as limma, DESeq2, edgeR, Seurat, or comparable tools.
• Familiarity with core Bioconductor data structures and packages such as SummarizedExperiment, SingleCellExperiment, GenomicRanges, and related infrastructure.
• Understanding of principles underlying normalization, batch effects, technical variability, biological variability, and quality-control assessment in omics datasets.
• Experience with exploratory data analysis and dimensionality-reduction methods such as PCA and clustering.
• Familiarity with next-generation sequencing and genomic variant analysis, including tools or workflows involving GATK, samtools, bcftools, VCF files, or VariantAnnotation.
• Familiarity with command-line tools and ability to work in a Linux/Unix environment.
• Experience using Git/GitHub or another version-control system.
• Ability to write organized, reproducible, and well-documented analysis code.
• Familiarity with statistical modeling frameworks (mixed-effects models).
• Ability to independently troubleshoot computational analyses and learn new analytical tools as project needs evolve.
• Strong analytical and problem-solving skills.
• Strong written and verbal communication skills and the ability to communicate computational results to researchers with different technical backgrounds.
• Ability to manage multiple analyses and research priorities in a collaborative environment.

Preferred Qualifications

• Master’s degree or Ph.D.

Pay

Salary Range: $55,200.00 - $100,000.00 / Annually

Benefits

• Up to 22 days of vacation, 10 recognized holidays, and sick time.
• Competitive health insurance packages with priority appointments and lower copays/coinsurance.
• Free Metro transit U-Pass for eligible employees.
• Defined contribution (403(b)) Retirement Savings Plan, combining employee contributions and university contributions starting at 7%.
• Wellness challenges, annual health screenings, mental health resources, mindfulness programs and courses, employee assistance program (EAP), financial resources, access to dietitians, and more.
• 4 weeks of caregiver leave to bond with a new child.
• Family care resources for childcare and adult care needs.
• Tuition coverage for employees and their families, including dependent undergraduate-level college tuition up to 100% at WashU and 40% elsewhere after seven years.