Research Collaboration
Advance the Science of Clinical AI
Modulus was built on three decades of research in artificial intelligence, data science, and high-performance computing. We have partnered with NASA, Oak Ridge National Laboratory, and leading research institutions around the world. That work continues, and we are looking for scientists who want to be part of it.
If you are researching clinical decision support, medical AI safety, health informatics, or related fields, we invite you to explore collaboration with Modulus.
Why Work With Us
Most healthcare AI companies are building wrappers around general-purpose language models and hoping for the best. We took a different path. Our clinical AI is purpose-built, backed by multiple internationally awarded patents for safe, accurate, and explainable recommendations. Every finding is traceable to peer-reviewed evidence. Every output is validated by a board-certified physician.
This architecture was designed not just for clinical use, but for rigorous study. We believe AI in healthcare must be held to the highest scientific standards, and we welcome researchers who want to help establish and verify those standards.
Research Opportunities
AI Safety and Reliability. Hallucination prevention, uncertainty quantification, and failure mode analysis in clinical AI systems. How do we ensure AI-generated health insights are accurate, and how do we detect when they are not?
Explainability and Interpretability. Methods for making clinical AI reasoning transparent to both physicians and patients. How do we build systems that show their work?
Clinical Validation. Studies measuring the real-world impact of AI-assisted care on diagnostic accuracy, time to diagnosis, and patient outcomes. Does this technology actually improve health?
Health Informatics. Medical record interoperability, data standardization, and the challenges of assembling complete patient histories from fragmented sources.
Human-AI Collaboration. How physicians interact with AI recommendations, when they override them, and how system design affects clinical decision-making.
Emerging Applications. Genomics integration, longitudinal health monitoring, predictive modeling, and other frontiers where clinical AI may deliver value.
What We Offer
Access to a production clinical AI system built for safety and traceability, not a research prototype. Collaboration with our team of AI researchers, data scientists, and clinical informaticists who have been working on these problems for decades.
Potential access to anonymized, aggregated data for approved research studies, subject to IRB approval and strict privacy protections. Co-authorship opportunities on peer-reviewed publications.
A partner that values scientific rigor over hype. We are not interested in publishing inflated claims. We want to advance the field.
Who Should Reach Out
Academic researchers in computer science, biomedical informatics, health services research, or related disciplines. Postdoctoral fellows and PhD candidates looking for industry collaboration or real-world data for dissertation research. Research physicians interested in studying AI-assisted clinical care.
Scientists at research institutions, national laboratories, or nonprofit research organizations. Industry researchers at organizations aligned with our mission of safer, more effective healthcare AI.
Our Commitment to Open Science
We believe the safety and efficacy of clinical AI should be subject to independent verification. While our core technology is proprietary, we are committed to publishing our methods, participating in external validation studies, and contributing to the broader scientific community's understanding of what works and what does not in medical AI.
Healthcare is too important for black boxes.