BIOINFORMATICS ANALYST JOB DESCRIPTION

Every sequencing run produces data. What determines whether that data becomes a published finding, a validated pipeline, or a dead end is the analyst who knows how to interrogate it. A Bioinformatics Analyst in academic and biomedical research owns the computational layer between raw genomic output and scientific knowledge, processing single-cell and bulk sequencing datasets, constructing reproducible analysis pipelines, and translating molecular results into interpretations that principal investigators and collaborators can act on. The role sits within research teams spanning cancer genomics, infectious disease, developmental biology, and multi-omics programs, often contributing directly to grant applications and peer-reviewed manuscripts. Staying current is not optional here.

As the Bioinformatics Analyst, you apply statistical and computational methods to high-throughput genomic and multi-omics datasets, converting sequencing data into reproducible findings that advance laboratory research programs and support publication outputs. You work within a research group alongside principal investigators, postdoctoral fellows, and wet-lab scientists, with scope ranging from single projects to coordinated support across multiple investigator teams.

Career Impact: Analysts who build expertise in scRNA-Seq, spatial transcriptomics, and NGS pipeline development establish a technical profile that is in high demand across academic medical centers and research institutes, positioning them for Senior Analyst and Lead Analyst advancement.

Business Impact: The reproducibility and accuracy of genomic findings submitted to public databases such as GEO and dbGaP, and cited in grant applications, depend directly on the analytical judgment this role exercises over every dataset it processes.

Growth Opportunity: Working across data modalities including whole genome sequencing, epigenomics, and liquid biopsy analysis gives analysts the cross-domain fluency needed to move into computational biology leadership or independent research scientist roles.

• Analyze single-cell and bulk genomic datasets from raw sequencing output through statistical interpretation, integrating in-house and public data across disease states and species.
• Design and maintain reproducible analysis pipelines for sequencing data types including RNA-seq, ChIP-Seq, scATAC-Seq, and digital spatial transcriptomics to ensure consistent output quality.
• Evaluate complex biological and technological covariates such as batch effects within large-scale genomic results to ensure valid downstream interpretation.
• Integrate multi-omics datasets and apply machine learning approaches to identify patterns at the gene, pathway, and systems level.
• Collaborate with principal investigators and research staff to guide experimental design, define analysis plans, and communicate findings through presentations and manuscript materials.
• Curate and submit genomic data to public repositories in compliance with institutional data-sharing policies, maintaining accurate version-controlled documentation throughout.
• Mentor and support junior staff, residents, and fellows on analytical methods, pipeline use, and result interpretation.
• Monitor pipeline performance and quality control metrics across concurrent projects, flagging anomalies and recommending corrective actions to research leads.

• Bachelor's degree in Bioinformatics, Computational Biology, Computer Science, or a related biological or quantitative discipline, or equivalent work experience.
• 2 or more years of experience in computational analysis of genomic or multi-omics datasets, with demonstrated proficiency in next-generation sequencing data processing.
• Proficiency in at least one scripting language such as R, Python, or Perl, applied to bioinformatics data manipulation and statistical analysis.
• Experience conducting quality control, sequence alignment, and variant or expression analysis within a Linux or Unix computing environment.
• Demonstrated ability to integrate datasets from public genomic databases including NCBI, Ensembl, or equivalent repositories for meta-analysis purposes.
• Ability to write and maintain clear version-controlled code and documentation using standard software development practices.
• Strong written and verbal communication skills with the ability to present technical findings to both computational and non-computational research collaborators.
• Proven organizational skills with the ability to manage timelines and deliverables across multiple concurrent research projects.

• Prior experience with single-cell sequencing modalities such as scRNA-Seq or spatial transcriptomics data, including familiarity with standard downstream analysis workflows.
• Background in a domain-relevant research area such as cancer genomics, infectious disease, developmental biology, or epigenomics, with exposure to the corresponding regulatory or experimental frameworks.
• Experience working in high-performance or cloud computing environments, including familiarity with job scheduling systems and containerized workflow managers.
• Record of contributing to peer-reviewed publications or grant application materials as a computational contributor.

• Pipeline reproducibility rate, measuring the proportion of analysis workflows that produce consistent output across independent runs.
• Manuscript and grant contribution count per year, reflecting the analyst's direct input into scientific output across supported research groups.
• Data submission accuracy to public repositories such as GEO or dbGaP, measured by the rate of accepted submissions without resubmission.
• Time from sequencing delivery to analysis-ready output, tracking how efficiently raw data is processed and staged for interpretation.
• Quality control pass rate across sequencing runs reviewed, indicating how reliably the analyst detects and flags anomalous data before downstream use.
• Typical tools: Scripting and statistical analysis (commonly R and Python), pipeline workflow managers (commonly Snakemake or Nextflow), version control (commonly Git).

• Base Salary Range: $65,000 to $105,000 per year depending on seniority and institution type.
• Bonus: Merit-based increases common; formal bonus structures less prevalent in academic settings.
• Equity: Rarely offered in academic or nonprofit research settings.
• Health Benefits: Medical, dental, and vision coverage standard through employing institution.
• PTO: 15 to 25 days annually, plus institutional holidays and sick leave.
• Common Perks: Tuition benefits, access to HPC resources, conference travel funding, and publication support.

Figures are estimates based on general US market benchmarks and may be outdated. Adjust based on location, company size, and seniority level.

Employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other characteristic protected under applicable federal, state, or local law. Candidates requiring reasonable accommodations during the application or interview process may request them at any time. Research environments with access to select agents or federally restricted data may require background screening and work authorization verification as a condition of employment. All applicants must be authorized to work in the United States.

The Bioinformatics Analyst owns the analysis and integration of single-cell and bulk genomic datasets, supporting research spanning stem cell differentiation, pediatric disease, and organoid-based cell therapy within the Division of Developmental Biology and CuSTOM at Cincinnati Children's Hospital Medical Center. Working closely with collaborative research groups, the analyst delivers reproducible results that advance high-impact publications and translational science across multiple investigator teams.

Key Responsibilities

• Perform data analysis for single-cell and bulk genomic datasets in collaboration with research groups.
• Conduct quality control, sequence alignment, statistical analyses, functional annotation, and network analysis.
• Integrate in-house and public datasets across patients, disease states, and species.
• Evaluate complex biological and technological covariates such as batch effects and sex from large-scale genomic results.
• Assess results at the gene, pathway, and systems level by integrating detailed biological knowledge.
• Customize data visualization using software toolkits such as R and Python.
• Apply existing software for sequence alignment, inter-sample comparison, algorithm evaluation, and data management.
• Document standard operating procedures based on best practices.
• Develop tools to support unsupervised sample and gene heterogeneity analyses.
• Guide, train, and support less-experienced staff, residents, fellows, and technologists.
• Manage interactions with research groups and coordinate efforts across projects at the Senior and Lead Analyst level.
• Prepare manuscript materials and present research findings at scientific meetings.

Required Qualifications

• Bachelor's degree in a relevant biological or computational discipline.
• 5 or more years of experience in bioinformatics, with positions available at Analyst, Senior Analyst, or Lead Analyst level depending on experience.
• Prior experience with large-scale bulk and single-cell genomics including scRNA-Seq, ChIP-Seq, scATAC-Seq, and WGS.
• Knowledge of state-of-the-art bioinformatics analytical methods with the ability to advance beyond them.
• Proficiency in biostatistics and at least one scripting language including R, Python, or Perl.
• Experience mining public genomic databases for meta-analysis and integration with in-house data.
• Demonstrated ability for clear version control documentation such as GitHub.
• Ability to work on Linux, Unix, and Windows environments, with familiarity with relational database and client-server concepts at Senior and Lead level.
• Excellent project and time management skills with the ability to prioritize and manage collaborator expectations.
• Excellent verbal and written communication skills including diverse data visualization approaches.

Embedded within the Battelle National Biodefense Institute federal laboratory sponsored by the Department of Homeland Security, the Bioinformatics Analyst delivers modular software workflows for genomic sequence processing, assembly, annotation, and genotyping across high-throughput sequencing platforms. Working closely with the bioinformatics group and biosafety teams, this analyst enables reproducible bioforensic sample analysis that directly supports national biodefense missions.

Core Functions

• Provide general bioinformatics analysis support for projects by integrating biological expertise and computational analyses.
• Develop, test, and maintain modular software workflows for genomic sequence processing, assembly, annotation, metagenomic analysis, and genotyping using high-throughput sequencing platforms.
• Manage genomic data including loading and querying from database systems, downloading from public repositories, and transforming into necessary formats.
• Adapt quickly to new assignments, demonstrate technical proficiency, and manage resources efficiently.
• Formulate scientific hypotheses and think independently to develop solutions.
• Maintain a safe work environment by participating in specialized training and reviewing safety manuals and SOPs.
• Develop techniques and perform analyses according to appropriate SOPs.
• Identify departures from the Quality Management System and initiate corrective actions.
• Serve as a team member in developing, validating, and maintaining methods for identifying and characterizing biological threat agents.

Qualifications and Experience

• Bachelor's degree in Bioinformatics, Computer Science, Computer Engineering, or Software Engineering with less than 2 years of experience in bioinformatics or a related discipline.
• Must be a citizen of the United States and able to obtain and maintain a top secret clearance with DHS suitability and DoJ favorable adjudication for select agent access.
• Strong biological background with demonstrated ability to interpret bioinformatic data.
• Familiarity with genomic sequence data and relevant software and databases for bioinformatic analysis.
• Expertise in operating in a UNIX/Linux environment with preferred fluency in Python, R, BASH, or Perl.
• Preferred familiarity with computing clusters and job management software such as SGE or SLURM.
• Knowledge or experience with biocontainment facilities, laboratory safety, biosurety, and decontainment.
• Skills to support laboratory activities in accordance with ISO-based management systems.
• Excellent written and oral communication skills with strong organizational skills and ability to work both independently and as a team player.

Reporting to the scientific leadership of the Health Analytics, Research, and Technology line of business, the Bioinformatics Analyst shapes the curation, harmonization, and analysis of clinical, genomic, proteomic, and metabolomic data from large-scale proteogenomic programs serving federal government clients. Partnering with scientists and database teams, this analyst advances the quality of scientific databases and directly enables reproducible multi-omics insights for cancer research programs.

Primary Duties

• Provide bioinformatics services to assist scientific problem-solving across a broad range of research topics.
• Analyze large molecular datasets including proteomic and genomic data for clinical and basic research purposes.
• Assist with data curation activities for scientific databases by working with scientists, conducting publication research, and performing verification.
• Support approaches and methods for the management, integration, analysis, and visualization of data from multiple sources.
• Assist in the management of genomic, proteomic, and other multiomic data and annotation resources.
• Standardize biomedical data using common data elements, terminologies, and controlled vocabularies.
• Develop custom scripts and software to automate scientific data analysis using Python, Perl/BioPerl, R, and Java.
• Assist in the development and maintenance of specialized high-performance databases for omics analysis.
• Operate and develop components for workflow management systems such as CWL, WDL, Snakemake, and Nextflow.

Education and Experience

• Master's degree in Biology, Biochemistry, or a related field with combined education and experience in bioinformatics; PhD preferred.
• One or more years of bioinformatics experience including programming in Perl, Python, R, or Java.
• Experience analyzing large-scale omics datasets such as genomics and proteomics.
• Experience in proteomics, genomics, metabolomics, or other related fields preferred.
• Thorough knowledge of Unix/Linux environments with ability to run and develop software.
• Experience with relational databases and graph databases is a plus.
• Experience working in a consulting firm, development organization, or public agency preferred.
• Perform statistical analyses using R, Python, or other open-source or commercial statistical applications.
• Effective written and oral communication skills with the ability to present technical ideas to stakeholders.

Sitting at the intersection of genomic pipeline development and clinical cancer research, the Bioinformatics Analyst supports the MoCha Laboratory within Leidos Biomedical Research's Clinical Research Directorate at the Frederick National Laboratory for Cancer Research. Operating across exome, whole genome, RNA-seq, single-cell, and digital spatial transcriptomics data, this analyst enables the development and application of genomic assays for NCI-sponsored national extramural clinical trials.

Duties

• Provide substantial bioinformatics support for the MoCha laboratory including analysis and interpretation of high-throughput genomic data.
• Validate and maintain genomic analysis pipelines for exome, whole genome, RNA-seq, single-cell RNA sequencing, and digital spatial transcriptomics data.
• Provide expertise in biological interpretation of results including mutation impact assessment, expression analysis, and statistics support.
• Prioritize identified loci and gene lists and build classification models to determine correlation with clinical data.
• Maintain and track complex data across multiple projects.
• Work with lab managers to update genetic information in databases.
• Provide support to lab staff in basic data analysis and study design.
• Coordinate and integrate software applications and databases across multiple NCI campuses.

Minimum Qualifications

• Bachelor's degree from an accredited college or university with a minimum of five years of progressively responsible experience.
• Experience in next-generation sequencing analysis including quality metrics, mapping, variant calling, biological interpretation, and large genomic data set integration.
• Hands-on experience analyzing DNA and RNA sequencing, expression, single-cell RNA sequencing, digital spatial transcriptomics, and array data.
• Proficiency in Unix/Linux systems and scripting languages such as Shell, R, Python, JavaScript, Perl, Java, SQL, and bioinformatics tools and database management.
• Ability to obtain and maintain a security clearance.
• Statistical analysis skills applied to complex biological data.
• Strong organizational skills and information tracking experience for data with complex structure.
• Excellent written and oral communication skills with demonstrated success in a team-oriented environment.

A key member of the Computational Biology Program in the laboratory of Dr. Gavin Ha at Fred Hutchinson Cancer Center, the Bioinformatics Analyst leads the analysis of cancer genomes to understand tumor progression, copy number alterations, genome rearrangements, and circulating tumor DNA from liquid biopsies. Collaborating across the Ha lab and external partners, this analyst enables breakthrough discoveries in tumor evolution and non-coding genome alterations that translate into manuscripts, presentations, and grant applications.

Accountabilities

• Analyze cancer genomes to understand tumor progression, evolution, heterogeneity, metastatic disease, non-coding genome alterations, copy number alterations, genome rearrangements, and 3D structure.
• Partner with scientists to refine computational research questions and design analytical processes for genomic datasets.
• Identify and implement bioinformatic tools for analyzing sequence data from tumor genomes including long-range sequencing technologies.
• Develop and apply computational approaches to analyze circulating tumor DNA from liquid biopsies.
• Prepare figures and written sections documenting methods and results for manuscripts, presentations, and grant applications.
• Interface with the Ha lab and collaborators to validate results using functional experiments.

Background and Experience

• Bachelor's degree in Computational Biology, Bioinformatics, Computer Science, Data Science, Statistics, Biostatistics, Biomedical Engineering, or a related field.
• 1 year of cumulative experience in computational analysis of large sequence-based molecular data.
• Previous experience working with cancer datasets is a strong asset.
• A background in cancer biology is a strong asset.
• Strong programming experience in R, Python, Matlab, Java, C/C++, Perl, or other research languages.
• Experience with analyzing genome sequencing data.
• Experience with high-performance computing or cloud computing environments is a strong asset.
• Strong communication skills with the ability to work well in team environments and attention to detail.

Accelerating the development of therapeutic clinical leads depends on the Bioinformatics Analyst at Sangamo Therapeutics, who builds and maintains analytical pipelines and web tools for gene expression, NGS experiments, and genome-scale hypothesis testing in a cross-functional therapeutics setting. Based within a collaborative team of cellular and molecular biologists, this analyst shapes decision-making by querying public omics resources and characterizing on-target and off-target profiles of gene-edited cellular products.

Technical Responsibilities

• Support and enable gene expression and NGS experiments by writing code that generates robust and interpretable results from sequencing data.
• Support genomics activities in a cross-functional therapeutics setting.
• Collaborate with cellular and molecular biologists to design functional genomics experiments for therapeutic target selection.
• Perform computational analyses to answer relevant biological questions.
• Generate and test hypotheses on genome-scale data using analytical and statistical methods.
• Query and integrate data from public omics resources to support decision-making.
• Maintain pipelines for analysis and display of protein evolution and gene expression data.

Skills and Qualifications

• Bachelor's degree in Bioinformatics, Biochemistry, Computer Science, Virology, Statistics, Bioengineering, or a related area, with 2-5 years of relevant experience; MS or PhD with less experience considered.
• Familiarity with sequencing platforms including Illumina, Affymetrix, bulk RNAseq, and single-cell sequencing, and NGS library preparation methods.
• Understanding of molecular biology processes, mammalian and viral genomes, and large-N experiments.
• Proficiency with computational methods to characterize on-target and off-target profiles and gene expression in gene-edited cellular products.
• Excellent Python and R programming skills with proficiency handling large-scale data in Linux and cloud environments such as AWS and DNAnexus.
• Familiarity with common NGS and genomics formats and resources including NCBI, UCSC, and EnsEMBL.
• Familiarity with at least one scientific graphics environment such as ggplot2, dash, matplotlib, scipy, seaborn, or D3.js.
• Git source code management experience, with experience using Docker and non-Illumina platforms such as PacBio, Oxford Nanopore, or Ion Torrent as a plus.
• Excellent communication skills with a strong sense of responsibility for generated data.

As the Bioinformatics Analyst, this role leads the development of new bioinformatic platforms and algorithms for oncology diagnostics, integrating internal and external multidimensional data across clinical NGS pipelines, raw microarray, genomic, and proteomics datasets. The oncology diagnostics team relies on this work to uncover novel findings that directly support diagnostic accuracy and the advancement of clinical research outcomes.

Role Responsibilities

• Lead the development of new bioinformatic platforms and algorithms for oncology diagnostics and data-mining.
• Develop and oversee clinical NGS pipelines and analysis on large molecular datasets including raw microarray data, genomic data, and proteomics data.
• Create and modify analytical and cloud-based bioinformatics tools to analyze and interpret multidimensional data.
• Conduct bioinformatic research and analysis independently and in close collaboration with the team.
• Integrate data internally and externally for interpretation and uncover novel findings.

Professional Experience

• Bachelor's degree or PhD in Bioinformatics, Biomathematics, Computational Biology, Statistics, or a related discipline.
• 3 or more years of experience in clinical NGS analysis.
• Proven publication record or demonstrated experience in NGS data processing and analysis using R, Python, Perl, Java, C++, or other programming languages.
• Strong time management and project management skills.
• Excellent written and oral communication skills in English and Mandarin.
• Strong communication skills with attention to detail and commitment to maintaining high standards of NGS analysis.

Bioinformatics Analyst evaluates and implements computational software for NGS-based infectious pathogen identification, genomic epidemiology, antimicrobial-resistance mapping, and phylogenetics, serving as a technical resource for senior epidemiologists, clinical laboratories, and local health authorities. The work directly supports accurate public health surveillance, proper diagnosis, and laboratory productivity improvements that inform state and national policy.

Day-to-Day Responsibilities

• Evaluate and implement bioinformatics computational software for analysis of NGS data including pipeline construction for infectious pathogen identification, genomic epidemiology, antimicrobial-resistance mapping, variant analysis, genome annotation, and phylogenetics.
• Consult with senior epidemiologists, clinical laboratories, and local health authorities on bioinformatics analysis results and make recommendations for further analysis and publications.
• Prepare results for release by ensuring accuracy within laboratory information management systems and other reporting systems.
• Monitor staff compliance with established policies and procedures for sequencing data analysis, quality metrics review, and results reporting.
• Perform quality control activities including verification, validation, routine quality control, and proficiency testing.
• Develop and apply tools for NGS data quality assessment and bioinformatics pipeline performance evaluation.
• Provide technical oversight to personnel performing sequencing analysis to ensure accurate surveillance, proper diagnosis, and improved laboratory productivity.
• Review laboratory testing processes and outcomes and make recommendations for revision and improvement.

Knowledge, Skills and Abilities

• Knowledge of microbiology, immunology, and molecular biology concepts and techniques including microbial culture, biochemical tests, serology, sequencing, and nucleic acid-based detection assays.
• Knowledge of quality assurance practices specific to microbiology and molecular biology test methods in a diagnostic setting.
• Knowledge of laboratory certifications and accreditations to ensure adherence to regulatory requirements.
• Ability to coordinate assignments for microbiological sample storage, handling, specimen retention, and packaging and shipping of infectious substances.
• Experience overseeing quality control activities and initiatives in a laboratory setting.
• Proficiency with technology including Microsoft Office programs such as Word, Excel, and PowerPoint.
• Strong communicator with the ability to establish productive working relationships with internal and external stakeholders.
• Ability to manage multiple projects accurately and on time in an environment with frequently changing deadlines.
• Excellent verbal and written communication skills with the ability to prepare concise technical reports and training presentations.

The Bioinformatics Analyst owns the planning, development, and continuous improvement of complex software applications for analyzing epigenetic datasets from Illumina iScan workflows, including Illumina HumanMethylation BeadChip data and integrated WGBS, ATAC-seq, and RNA-seq datasets. Working closely with research scientists and publication teams, this analyst delivers analysis, documentation, and reporting that enables rigorous epigenomics research and supports scientific publications and presentations.

Scope of Work

• Provide statistical and computational tools for biologically based activities such as genetic analysis, gene expression measurement, and gene function determination.
• Plan, develop, and continuously improve complex software applications capable of analyzing epigenetic datasets from Illumina iScan workflows.
• Analyze large molecular datasets including raw microarray data, genomic sequence data, and Illumina HumanMethylation BeadChip datasets across different species.
• Assess, develop, and implement strategies to integrate Illumina HumanMethylation BeadChip workflows.
• Integrate and manage large data volumes in MySQL databases.
• Coordinate projects for the integrative analysis of WGBS, ATAC-seq, and RNA-seq datasets.
• Perform analysis, document findings, and write reports on research results.
• Support the preparation of scientific publications, presentations, and posters.

Experience and Qualifications

• PhD in Computational Biology, Bioinformatics, Computational Chemistry, or a closely related field.
• 3-5 years of experience in molecular biology and genetics, standard bioinformatics databases and algorithms, or pathway and protein structure and interaction databases.
• Broad hands-on experience in bioinformatics programming including shell scripting, object-oriented programming in R or Python, and experience with RDBMS systems such as PostgreSQL and MySQL.
• Work experience in industry or as an academic post-doc is a plus.
• Strong analytical and problem-solving skills with scientific creativity.
• Excellent verbal and written communication skills, fluent in English.
• Clear sense of organization, purpose, and accountability with concise reporting.
• Ability to work in a fast-paced, matrix, and team-oriented environment while self-motivated in leading scientific projects.

Embedded within the Michael Group in the Plant Biology Laboratory at the Salk Institute, the Bioinformatics Analyst builds and maintains analysis pipelines for plant genome assembly, gene prediction, gene set annotation, and multi-omic data integration in a cloud computing environment. Working closely with researchers from multiple laboratories and scientific backgrounds simultaneously, the analyst advances high-throughput plant genomics research that contributes to manuscripts, grant applications, and scientific conference presentations.

Job Functions

• Contribute to project inception, experimental design, analysis, and result presentation.
• Assist with the preparation of data for manuscripts, publications, grant applications, posters, and other presentations.
• Assemble plant genomes, predict genes, annotate gene sets, and integrate multi-omic datasets in collaboration with lab researchers and collaborators.
• Use published pipelines, scripts, and tools to prepare and process large datasets in a cloud computing environment.
• Research, implement, test, and present new tools and pipelines for high-throughput data analysis.
• Participate in the design and coding of analysis pipelines and novel data analysis algorithms.
• Provide assistance and training to researchers on how to analyze and interpret plant genome data.
• Help maintain scripts, software, tools, wikis, and pipelines, and ensure servers and cloud instances are operating properly.

Technical Qualifications

• Bachelor's degree in Bioinformatics, Computational Biology, Computer Science, Biological Sciences, Bioengineering, Mathematics, Statistics, or a related discipline; MS or PhD preferred.
• 0-3 years of related experience, with 6 months of genome analysis experience or 1 year of multi-omics analyses experience.
• Familiarity with next-generation sequencing technologies, assays, and cloud computing and containerization.
• Experience with analyzing plant genomes and plant biology, and background in machine learning algorithms and computational modeling preferred.
• Programming experience in Perl, Bash, Python, C/C++, Java, or R with high proficiency in at least one scientific programming language.
• Experience working in a Linux/UNIX operating system in a high-performance computing environment.
• Strong communication skills both verbal and written, with the ability to explain difficult concepts and train users and students.
• Proven organizational and time management skills to successfully set priorities and meet established deadlines.
• Ability to interact diplomatically and professionally with all levels of institute staff and external contacts.

The Bioinformatics Analyst delivers end-to-end data management pipelines for next-generation sequencing data spanning transcriptomics, proteomics, epigenetic data, and microbiome 16S RNA across multiple labs within NCI/CCR's Vaccine Branch. Working closely with the CCBR team, Vaccine Branch researchers, and CCR-IT, this analyst enables experimental design guidance, data submission compliance, and high-quality manuscript preparation that advances cancer and immunotherapy research.

Strategic Responsibilities

• Develop, manage, and maintain data management pipelines for next-generation sequencing data across multiple labs including transcriptomics, proteomics, epigenetic data, and microbiome 16S RNA.
• Collect, review, analyze, and interpret data and results, and provide reports to make recommendations for future work.
• Work with the CCBR team to adopt best practices for analysis of various NGS data.
• Support staff with data visualization to assist in the preparation of presentations and manuscripts for scientific journals.
• Consult with Vaccine Branch members to guide experimental design and carry out primary and secondary data analysis.
• Liaise between the Vaccine Branch and CCR-IT to resolve network and IT issues related to software and hardware integrity.
• Assist PIs in submitting data to public genomic databases such as GEO and dbGaP in compliance with NIH Genomic Data Sharing Policy.
• Process data using NIH Biowulf computer clusters in batch mode.
• Train postdocs and other staff to use NGS and other genomic analysis tools, and advise on available data analysis pipelines.

Required Qualifications

• Bachelor's degree in Computer Science, Math, or a Biomedical Science-related field, or four years of relevant experience instead of degree; Master's or PhD in a Biomedical field preferred.
• Minimum of two years of progressively responsible experience for Analyst II, or five years for Analyst III.
• Ability to obtain and maintain a security clearance.
• Experience in bioinformatics, computational biology, or cancer genomics, with research knowledge of immunology, virology, or a related field.
• Experience in at least two of the following: exome or panel sequencing, RNA-Seq, whole genome sequencing, copy number analyses, or gene expression data.
• Experience designing and creating bioinformatics pipelines for genomics analysis and evaluating different computational pipelines for alignment, variant calling, and functional annotation.
• Good understanding of Next Generation Sequencing data analysis and computer functionality in PC, MAC, and Linux environments.
• Leadership characteristics with the ability to mentor and direct postdoctoral fellows and trainees in bioinformatics.
• Strong oral and written communication skills with excellent organizational and time management skills.

Reporting to the Malaria Research Program leadership within the Center for Vaccine Development and Global Health at the University of Maryland School of Medicine, the Bioinformatics Analyst develops and executes pipelines to manage genomic, transcriptomic, proteomic, and immunological data while providing technical leadership across large-scale, multi-member project teams. Partnering with the Institute for Genome Sciences and international collaborators, this analyst advances malaria prevention, treatment, and surveillance research that directly supports improvements in global health outcomes.

Ownership Areas

• Develop and execute pipelines to manage various data types including processing, quality assurance of raw data, and transforming data into necessary formats for downstream analysis.
• Organize omics data with relevant metadata in relational databases and develop tools to query and visualize available data.
• Integrate and analyze systems data using statistical and machine learning approaches.
• Communicate analytical strategies and results verbally and in writing in support of presentations, publications, reports, and grant applications.
• Provide technical leadership to multiple ongoing projects simultaneously and to large-scale, multi-member project teams.
• Participate in capacity building and training of international collaborators and MRP trainees at various levels.
• Work with IGS and School of Medicine IT staff to maintain up-to-date programs and packages for the CVD Linux-based server.

Experience and Qualifications

• Bachelor's degree in Computer Science, Information Technology, Bioinformatics, or Life Sciences including Biology, Molecular Biology, Genetics, or Biochemistry.
• Eight years of genomic research experience in Windows and UNIX-based environments with direct experience in genomic data QC, assembly, annotation, and analysis of various data types, including four years of large-scale project management experience and two years at a leadership level.
• Knowledge of bioinformatics tools and public databases used for omics-based data manipulation and analysis.
• Demonstrated experience developing web-based tools, databases, or bioinformatics applications within teams.
• Demonstrated knowledge of multiple omics-based approaches applied to molecular biology, microbiology, genetics, or infectious disease research.
• Machine learning and data science experience is desirable.
• Excellent oral and written communication, presentation, organization, and time management skills.
• Strong interpersonal skills with the ability to effectively interact with all levels of staff and domestic and international collaborators.

A key member of the Allen Institute for Cell Science, the Bioinformatics Analyst builds reproducible pipelines to analyze single-cell transcriptomics scRNA-Seq data from FASTQ through downstream analyses and integrates these with imaging data including RNA-FISH to support team-based scientific programs. Collaborating across interdisciplinary teams within and outside the AICS community, this analyst enables novel datasets that elucidate cellular states and advance the institute's cell biology research mission.

Activities

• Analyze single-cell transcriptomics scRNA-Seq data from FASTQ through alignment and subsequent downstream analyses.
• Build and support bioinformatic tools and reproducible pipelines to support team-based scientific programs.
• Assist with creating workflows to enable data sharing internally and externally.
• Work across teams to integrate scRNAseq data with imaging data including RNA-FISH to support scientific projects and programs.
• Communicate the impact of work through presentations, dissemination, and research papers within and outside the AICS community.

Skills and Qualifications

• Bachelor's degree or Master's degree in Biology, Computational Biology, Bioinformatics, Computer Science, Biostatistics, Physics, or Applied Math.
• Experience with computational analysis of biological datasets and analyzing RNA-seq, exome, whole genome, or related sequencing data types in population and single cells.
• Knowledge of genomic experimental and analytical methods including different sequencing technologies, common NGS analysis tools, and workflow managers such as STAR, Seurat, Monocle, and Snakemake.
• Knowledge of multiplexed RNA-FISH methods and spatial transcriptomics.
• Expertise with bash and at least one programming language such as Python or R, along with experience with Git, Jupyter, and RStudio.
• Expertise with Linux environment, high-performance cluster computing, and command line interfaces.
• Knowledge of open-source genomics databases and resources such as UCSC Genome Browser, Ensembl, and OMIM.

Sitting at the intersection of spatial transcriptomics and molecular immunology, the Bioinformatics Analyst at the Allen Institute for Immunology develops and standardizes processing and analytical pipelines for spatial transcriptomics data and imaging data while supporting wet-lab scientists on technology enhancement. Operating across multiple concurrent projects with production deadlines, this analyst enables rigorous bioinformatic support that advances institute research programs in immunological cell states.

Work Activities

• Perform hands-on analysis of clinical and molecular omics data including spatial transcriptomics data and imaging data.
• Develop and standardize processing and analytical pipelines for spatial transcriptomics data and imaging data.
• Implement and streamline in-house or open-source analysis pipelines including quality control and data mining for spatial transcriptomics data.
• Support wet-lab scientists on technology enhancement and development.
• Meet production deadlines for data analysis and pivot between multiple projects as needed.
• Contribute to a rigorously scientific, cohesive, and efficient team environment.

Position Requirements

• Bachelor's degree in Bioinformatics or a closely related discipline with 0-2 years of equivalent experience.
• Hands-on experience analyzing high-throughput RNA-seq data, NGS data, or proteomics data.
• Track record of implementing analysis pipelines for omics data.
• Experience with single-cell sequencing data and spatial transcriptomics or imaging data.
• Knowledge in high-throughput technologies and immunology.
• Fluency in R, Python/Perl, Linux operating system, and shell scripting.
• Working knowledge of cloud computing and version control systems such as Git.
• Excellent written and verbal communication skills and organizational skills.

As the Bioinformatics Analyst, this role executes large-scale sequencing dataset management, data manipulation using Python, Perl, and UNIX tools, and variant annotation using genome browsers and open-source databases, providing direct consultation to UVA investigators on experimental design and manuscript preparation. The genomics research community relies on this work to maintain high-throughput analytical capacity across RNA-seq, ChIP-seq, ATAC-Seq, and metagenomics projects.

Key Deliverables

• Organize and manage large-scale sequencing datasets.
• Manipulate and format data using Python, Perl, and UNIX tools.
• Use established open-source software and tools to assess quality and analyze data.
• Run analyses on a high-performance computing cluster.
• Use software or genome browsers for visualization and annotate genetic variants and results from expression and epigenetics experiments.
• Consult with investigators on experimental design, result interpretation, and grant and manuscript preparation.

Education and Experience

• Bachelor's degree in Bioinformatics, Genomics, Biostatistics, Computer Science, or a related field with at least three years of relevant experience; Master's degree considered in lieu of experience.
• PhD in Bioinformatics, Genomics, Biostatistics, Computer Science, or a related field with five years of specialized experience preferred.
• Strong knowledge of working in a Unix/Linux environment and experience with high-performance computing.
• Advanced proficiency with R/Bioconductor, Python, or C/C++.
• Experience with open-source software, tools, and databases for analyzing NGS data including RNA-seq, ChIP-seq, ATAC-Seq, DNA variation, epigenetics, microbiome, and metagenomics.

Translational insights that connect clinical genomic data to cancer therapy response depend on the Bioinformatics Analyst, who designs and performs analyses of omics data and clinical variables to discover biomarkers for response and resistance to therapy in oncology clinical trials. Serving as a computational partner to clinical trial teams and research teams, this analyst refines innovative analytical approaches with direct impact on candidate biomarker interpretation and translational decision-making.

Performance Expectations

• Support genomic biomarker profiling studies in oncology clinical trials.
• Design and perform analyses of omics data and clinical variables to test and discover biomarkers for response and resistance to therapy.
• Develop and implement innovative analytical approaches with translational impact for clinical genomic data.
• Assess quality control metrics and provide biological interpretation of biomarkers.
• Communicate key findings and biological context to clinical trial teams and research teams.

Qualifications and Experience

• Master's degree with 2 or more years of experience, or PhD in Computational Biology, Bioinformatics, Biology, Computer Science, or a related field.
• Hands-on experience with data processing, analysis, integration, and interpretation across different NGS and omics experiments.
• Familiarity with fundamental concepts in cancer genomics, statistics, bioinformatics, and machine learning approaches.
• Knowledge of oncology, clinical, and translational science preferred, with experience applying machine learning approaches to complex biological questions preferred.
• Demonstrated statistical and analytical ability with programming expertise in R and Python.
• Excellent interpersonal and communication skills with proven ability to work effectively within a team and take ownership of challenging problems.

Bioinformatics Analyst refines the full spectrum of computational sequence analysis support for researchers, including data extraction and preparation from multiple platforms, installation and customization of analytical software on research clusters, and performance assessment to ensure maximum productivity and scientific validity. The work directly supports researchers across ongoing projects and contributes to grant writing, quality control documentation, and adoption of emerging bioinformatics tools and best practices.

Operational Focus

• Provide experienced consultation and employ computational sequence analysis tools to model and analyze biological data in support of researchers.
• Access, extract, and prepare data for analysis including combining data from multiple platforms and externally generated data for meta-analyses.
• Install, configure, customize, and support analytical software for data on research clusters, and develop software and programming scripts for workflow systems.
• Undertake performance and reliability assessments to ensure systems are operating at maximum productivity and scientific validity.
• Document consultation, analysis, and quality control efforts, and contribute to grant and report writing.
• Research and stay up to date on emerging technologies, tools, trends, standards, and best practices in bioinformatics.

Background and Experience

• Bachelor's degree in Computer Science, Bioinformatics, Biology, or a related field; Master's degree preferred.
• 2 years of experience in research technology support, large biological data analysis, or a related role.
• Proficient communication skills with a high degree of professionalism and commitment to quality.
• Demonstrated time management and priority-setting skills with flexibility to work in a fast-paced environment.
• Highly thorough and dependable with a high level of accuracy under pressure.