Bioinformatics/Data Scientist

(ID: 2025-0696) Axle is a bioscience and information technology company that offers advancements in translational research, biomedical informatics, and data science applications to research centers and healthcare organizations nationally and abroad. With experts in biomedical science, software engineering, and program management, we focus on developing and applying research tools and techniques to empower decision-making and accelerate research discoveries. We work with some of the top research organizations and facilities in the country including multiple institutes at the National Institutes of Health (NIH). Axle is seeking a Bioinformatics/Data Scientist to join our vibrant team at the National Institutes of Health (NIH) supporting the Standardized Organoid Model Center in Frederick, MD. The Standardized Organoid Model Center is an NIH-funded initiative dedicated to advancing organoid research through the development of validated, reproducible, and well-characterized organoid models. The center brings together interdisciplinary teams of researchers to establish standardized protocols, develop quality control measures, and create resources that will benefit the broader organoid research community. Benefits We Offer: 100% Medical, Dental & Vision Coverage for Employees Paid Time Off and Paid Holidays 401K match up to 5% Educational Benefits for Career Growth Employee Referral Bonus Flexible Spending Accounts: Healthcare (FSA) Parking Reimbursement Account (PRK) Dependent Care Assistant Program (DCAP) Transportation Reimbursement Account (TRN) Cover Letter Required — Please Answer the Following Questions and Submit Application at: Bioinformatics/Data Scientist To be considered for this position, please upload a document as your Cover Letter that answers the six questions below. Applications submitted without this document will not be considered. What experience do you have working with large datasets and compute clusters? Describe your experience building workflows/pipelines and/or using bioinformatics software and tools to analyze data. What programming languages are you comfortable using for bioinformatics data analysis? What bioinformatics areas are you familiar with? (e.g., single cell, bulk genomics, transcriptomics, epigenetics, flow, spatial, metagenomics, etc.) What life science disciplines do you have experience in? (e.g., immunology, infectious disease, cancer research, etc.) Provide examples of basic machine learning/AI concepts and/or how you've applied them in bioinformatics data analysis. Overview The Bioinformatics/Data Scientist will conduct comprehensive analyses of multi-omics data generated from organoid systems and corresponding normal tissues. This position is central to the SOM Center's research objectives, focusing on characterizing organoid fidelity, identifying biomarkers of successful differentiation, and developing computational frameworks for organoid quality assessment. Responsibilities The successful candidate will analyze complex datasets including single-cell RNA sequencing, bulk RNA sequencing, proteomics, and metabolomics data from various organoid systems and their tissue counterparts. The position will develop and implement computational pipelines for data processing, quality control, and statistical analysis. A major component of the role involves integrating SOM-generated data with publicly available datasets to benchmark organoid characteristics against normal tissue profiles. The position requires close collaboration with experimental teams to interpret results and guide protocol optimization, as well as contributing to manuscript preparation and presenting findings at scientific conferences. Required Qualifications Candidates must hold a PhD in bioinformatics, computational biology, biostatistics, or a related quantitative field. Extensive experience with single-cell data analysis, including familiarity with tools such as Seurat, Scanpy, or similar platforms, is essential. Strong programming skills in R and Python are required, along with experience in statistical analysis and data visualization. Knowledge of proteomics and metabolomics data analysis workflows is necessary. Preferred Qualifications Previous experience analyzing organoid datasets is strongly preferred. Experience with machine learning approaches for biological data, familiarity with pathway analysis tools, and knowledge of developmental biology principles will be considered valuable assets. Experience with high-performance computing environments and version control systems is desirable. Disclaimer: The above description is meant to illustrate the general nature of work and level of effort being performed by individuals assigned to this position or job description. This is not restricted as a complete list of all skills, responsibilities, duties, and/or assignments required. Individuals may be required to perform duties outside of their position, job description or responsibilities as needed. The diversity of Axle’s employees is a tremendous asset. We are firmly committed to providing equal opportunity in all aspects of employment and will not tolerate any illegal discrimination or harassment based on age, race, gender, religion, national origin, disability, marital status, covered veteran status, sexual orientation, status with respect to public assistance, and other characteristics protected under state, federal, or local law and to deter those who aid, abet, or induce discrimination or coerce others to discriminate. Accessibility: If you need an accommodation as part of the employment process please contact: careers@axleinfo.com This role has a market-competitive salary with an anticipated base compensation range listed below. Actual salaries will vary depending on a candidate’s experience, qualifications, skills, and location. #IND Salary Range $105,000 — $120,000 USD