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).
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)
Position Overview
The Research Data Manager will build and maintain the data infrastructure for the SOM Center. This includes the Laboratory Information Management System (LIMS), document and repository platforms such as Invenio, and the metadata databases and pipelines that connect them. The role brings together instrument, assay, and analysis data and makes it findable, traceable, and reusable, in line with NIH data management and sharing requirements. The position combines hands-on software development with data stewardship, using cloud-native tooling and AI/ML to make data easier to find and use.
Key Responsibilities
Data integration. Connect laboratory instruments, analysis pipelines, and external data sources to the LIMS. Build and maintain automated ingestion pipelines with validation, logging, and error handling.
Data wrangling and format conversion. Write and maintain custom scripts and services that convert, normalize, and harmonize heterogeneous data formats (instrument exports, imaging metadata, omics outputs, spreadsheets) into standardized schemas.
Repository and document management. Deploy, configure, and support document and research data management systems such as Invenio. Manage records, metadata schemas, persistent identifiers, and access controls.
Database development. Design, create, and maintain databases for experimental metadata and small-to-moderate datasets, including schema design, migrations, indexing, and backup and recovery.
AI/ML-assisted discovery. Incorporate ML/AI into data workflows and user interfaces, such as semantic search, metadata extraction and auto-annotation, and natural-language query tools, to help researchers find and use data.
Platform and cloud engineering. Develop, containerize, and deploy software solutions on cloud or local Kubernetes resources. Maintain CI/CD pipelines, monitoring, and infrastructure-as-code.
Tool evaluation. Evaluate and recommend packages, platforms, and standards for data management, and prepare short technical assessments for IDSS leadership.
Training and documentation. Train laboratory and analytical staff, and write standard operating procedures and technical documentation.
Required Qualifications
Data integration. Connect laboratory instruments, analysis pipelines, and external data sources to the LIMS. Build and maintain automated ingestion pipelines with validation, logging, and error handling.
Data wrangling and format conversion. Write and maintain custom scripts and services that convert, normalize, and harmonize heterogeneous data formats (instrument exports, imaging metadata, omics outputs, spreadsheets) into standardized schemas.
Repository and document management. Deploy, configure, and support document and research data management systems such as Invenio. Manage records, metadata schemas, persistent identifiers, and access controls.
Database development. Design, create, and maintain databases for experimental metadata and small-to-moderate datasets, including schema design, migrations, indexing, and backup and recovery.
AI/ML-assisted discovery. Incorporate ML/AI into data workflows and user interfaces, such as semantic search, metadata extraction and auto-annotation, and natural-language query tools, to help researchers find and use data.
Platform and cloud engineering. Develop, containerize, and deploy software solutions on cloud or local Kubernetes resources. Maintain CI/CD pipelines, monitoring, and infrastructure-as-code.
Tool evaluation. Evaluate and recommend packages, platforms, and standards for data management, and prepare short technical assessments for IDSS leadership.
Training and documentation. Train laboratory and analytical staff, and write standard operating procedures and technical documentation.
Preferred Qualifications
Experience deploying or customizing Invenio/InvenioRDM or similar repositories (Dataverse, DSpace, CKAN).
Experience integrating ML/AI components into applications, such as embeddings and vector search, LLM-based retrieval, or document parsing.
Familiarity with workflow tools (Airflow, Nextflow, Snakemake, Argo) and with Helm, Terraform, or similar infrastructure-as-code tools.
Experience with stem cell or tissue engineering laboratories.
Experience with imaging and omics data.
Experience with high-performance computing environments (for example NIH Biowulf).
Experience with front-end tooling (React or similar) for data-facing interfaces.
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: [email protected]
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.
Skills Required
- Connect laboratory instruments, analysis pipelines, and external data sources to a LIMS; build automated ingestion pipelines with validation, logging, and error handling.
- Write and maintain scripts and services for converting, normalizing, and harmonizing heterogeneous data formats into standardized schemas.
- Deploy, configure, and support research data repositories and document-management systems such as Invenio; manage records, metadata schemas, persistent identifiers, and access controls.
- Design, create, and maintain databases for experimental metadata and small-to-moderate datasets, including schema design, migrations, indexing, backup, and recovery.
- Incorporate AI/ML into data workflows and interfaces, including semantic search, metadata extraction, auto-annotation, and natural-language query tools.
- Develop, containerize, and deploy software on cloud or local Kubernetes resources; maintain CI/CD pipelines, monitoring, and infrastructure-as-code.
- Evaluate data-management packages, platforms, and standards and prepare technical assessments for leadership.
- Train laboratory and analytical staff and write standard operating procedures and technical documentation.
- Experience deploying or customizing Invenio, InvenioRDM, or similar repositories such as Dataverse, DSpace, or CKAN.
- Experience integrating ML/AI components into applications, including embeddings, vector search, LLM-based retrieval, or document parsing.
- Familiarity with workflow tools such as Airflow, Nextflow, Snakemake, or Argo, and infrastructure-as-code tools such as Helm or Terraform.
- Experience with stem cell or tissue engineering laboratories.
- Experience with imaging and omics data.
- Experience with high-performance computing environments such as NIH Biowulf.
- Experience with front-end tooling such as React or similar technologies for data-facing interfaces.
What We Do
Axle Informatics is a bioscience and information technology company that offers advancements in translational research, health informatics, and data science applications to research centers and healthcare organizations around the globe. With experts in biomedical science, software engineering, and program management, we develop and apply research tools and techniques that 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) by offering the responsiveness of a small business coupled with the experience, breadth, and depth of a large organization.
