> Markdown version of [/jobs/ext/3975392-nspectra-ai-modeling-and-federated-data-platforms](https://www.wearedevelopers.com/jobs/ext/3975392-nspectra-ai-modeling-and-federated-data-platforms). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# nSPECTRA AI Modeling and Federated Data Platforms

- **Company:** Nspectra
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Health Informatics, Cloud Computing, Computer Simulation, Data Governance, Interoperability, Machine Learning, Cloud Platform System, High Performance Computing, Fast Healthcare Interoperability Resources, Distributed Learning, Information Technology, Machine Learning Operations
- **Published:** October 27, 2026
- **Apply:** https://jobs.military.com/career/376805/spectra-ai-modeling-federated-data-platforms-ta2-seta-26-166-virginia-va-arlington

## About the Role

u2022 Minimum five years of experience post-doc.\n
\u2022 Experience developing or evaluating machine learning and computational models with real-world health or biomedical data\n
\u2022 Experience with federated or distributed learning, or with other privacy-preserving computation on sensitive data\n
\u2022 Experience with longitudinal or causal modeling methods (e.g., trajectory or mixed-effects models, survival analysis, causal inference, causal ML)\n
\u2022 Experience with budgeting and program or project management\n
\n
\nExperience/Expertise Preferred:\n
\u2022 Experience building or running multi-site research data networks (e.g., OHDSI, PCORnet, N3C, or federated genomics consortia)\n
\u2022 Data standards and interoperability (e.g., OMOP CDM, HL7 FHIR, GA4GH)\n
\u2022 Multimodal and foundation-model approaches for combining sensor, audio, video, language and 'omics data\n
\u2022 Familiarity with health data governance and privacy requirements (HIPAA, and FERPA for school data), consent and assent for minors, and data use agreements\n
\u2022 Responsible AI frameworks and regulatory context (e.g., NIST AI RMF, FDA guidance on AI-enabled medical devices)\n
\u2022 Engineering for scalable platforms: cloud and high-performance computing, MLOps, security\n
\u2022 Autism or neurodevelopmental data and research\n
\u2022 Participatory or community data governance, i.e., giving autistic people and families a say in how their data and models are used\n
\u2022 Lived experience of autism is a plus. Disclosure is voluntary and not required.\n, u2022 PhD in computer science, machine learning, statistics or biostatistics, biomedical informatics, applied mathematics, electrical engineering, or a related field. A master's degree with substantial relevant research or industry experience may be considered.\n