Bioinformaticist - Neurology
Washington University in St. Louis
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Benefits offered by this job
Job summary
Washington University in St. Louis is seeking a talented data scientist to support computational and quantitative research on aging, neurodegeneration, and human disease.
The role involves developing scalable workflows and analyzing diverse omics data to derive actionable biological insights. You will collaborate with bioinformatics scientists, experimental researchers, and external partners to interpret complex datasets, publish results, and contribute to grant proposals.
Qualifications
- Bachelor's degree required; master's/PhD preferred.
- Experience with high-dimensional omics data analysis.
- Proficiency in R and Bioconductor ecosystems.
Responsibilities
- Design and implement omics data analysis workflows.
- Perform quality control, normalization, and feature selection.
- Apply dimensionality reduction, clustering, and cell-type annotation.
- Integrate multi-omics data and visualize results.
- Collaborate with wet-lab scientists and contribute to manuscripts.
Skills
Education
Tools
Job description
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. The candidate will contribute to the full analytical workflow, including data quality assessment, preprocessing and normalization, statistical modeling, dimensionality reduction, network analysis, multi‑omic integration, visualization, and biological interpretation.
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.
SAINT LOUIS, MO 63110
40
- Algorithms and computer software for omics-based data sets [high-throughput, massively parallel genomic/proteomic/clinical.].
- Data management and analysis solutions that aid in the storage, investigation, and dissemination of large data sets.
- Independent research projects, including design of research protocols and development of procedures for the collection, verification, and management of data.
- Develop clear, informative, and publication-quality data visualizations, including heatmaps, dimensionality-reduction plots, statistical summaries, pathway/network visualizations, and other figures appropriate for scientific communication.
- Perform data quality control, preprocessing, normalization, filtering, identifying technical artifacts, outliers, batch effects, and other sources of unwanted variation.
- Perform 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
- Analyze 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.
- Work 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.
Job Location/Working Conditions
- Normal Office Environment
Physical Effort
- Typically Sitting at a desk or table
Equipment
- Office Equipment
The above statements are intended to describe the general nature and level of work performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all job duties performed by the personnel so classified. Management reserves the right to revise or amend duties at any time.
Required Qualifications: Bachelor's degree
No specific certification/professional license is required for this position.
Research (4 Years)
Not Applicable
A driver's license is not required for this position.
- 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, Ph.D. - Doctor of Philosophy
No additional certification/professional licenses unless stated elsewhere in the job posting.
No additional work experience unless stated elsewhere in the job posting.
Analytical Thinking, Big Data Processing, Bioinformatics Tools, Communication, Complex Data Analysis, Computational Biology, Critical Reasoning, Data Management, Discrete Mathematics, Group Problem Solving, Java (Programming Language), Machine Learning (ML), Perl Programming, Probabilistic Modeling, Python (Programming Language), Statistics
R11
$55,200.00 - $100,000.00 / 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.
For frequently asked questions about the application process, please refer to our External Applicant FAQ.
If you are unable to use our online application system and would like an accommodation, please email CandidateQuestions@wustl.edu or call the dedicated accommodation inquiry number at 314-935-1149 and leave a voicemail with the nature of your request.
All qualified individuals must be able to perform the essential functions of the position satisfactorily and, if requested, reasonable accommodations will be made to enable employees with disabilities to perform the essential functions of their job, absent undue hardship.
All external candidates receiving an offer for employment will be required to submit to pre-employment screening for this position. The screenings will include criminal background check and, as applicable for the position, other background checks, drug screen, an employment and education or licensure/certification verification, physical examination, certain vaccinations and/or governmental registry checks. All offers are contingent upon successful completion of required screening.
- 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 challenges, annual health screenings, mental health resources, mindfulness programs and courses, employee assistance program (EAP), financial resources, access to dietitians, and more!
- 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.
For policies, detailed benefits, and eligibility, please visit: https://hr.wustl.edu/benefits/
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, 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.
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