AI Research Engineering (Translational Genomics & Multi-Omic Data Platforms) in Norwalk

The Multiple Myeloma Research Foundation (MMRF) has developed Virtual Lab, a next- cloud research platform and data commons designed to enable scientists to explore, analyze, and collaborate around large-scale genomic and clinical datasets related to multiple myeloma.

Built on the Gen3 data commons framework and deployed on AWS, Virtual Lab supports secure data access, computational workflows, and advanced analytical applications used by the global multiple myeloma research community.

This will engage with a project supporting the introduction of AI applications to the Virtual Lab platform. The will work directly with the Translational Research engineering team to enhance the platform, prototype new analytical capabilities, and expand the technical foundation supporting large-scale biomedical data analysis.

• Currently pursuing a Master's or PhD in Computer Science, Software Engineering, Data Science, Computational Biology, or a related technical discipline.
• Strong programming ability (3+ years) in Python or another modern programming , with familiarity with software engineering best practices and version control systems (e.g., Git).
• Interest in building software systems for scientific or data-intensive applications.
• Strong problem-solving ability, intellectual curiosity, and interest in applying technology to advance biomedical research.
• Experience (1-2 years) with cloud computing environments (e.g., AWS, GCP, Azure) and containerization (Docker).
• : Exposure to data analysis, scientific computing, or machine learning tools.
• : Familiarity with genomics, bioinformatics workflows, biomedical datasets, or research software development.
• : Experience building APIs or data visualization tools.

The Multiple Myeloma Research Foundation (MMRF) is the largest nonprofit in the world solely focused on accelerating a cure for each and every multiple myeloma patient. We drive the development and delivery of next- therapies, leverage data to identify optimal and more personalized treatment approaches, and empower myeloma patients and the broader community with information and resources to extend their lives. Central to our mission is our commitment to advancing health equity so that all myeloma patients can benefit from the scientific and clinical advances we pursue. Since our inception, the MMRF has committed over $600 million for research, opened nearly 100 clinical trials, and helped bring 15+ FDA-approved therapies to market, which have tripled the life expectancy of myeloma patients. To learn more, visit www.themmrf.org. MMRF Core Values: At the MMRF our core values define both who we are and how we work together as an organization. We believe in investing in our team and building a culture that will help us pursue our highest level mission to accelerate a cure for each and every multiple myeloma patient. Our five core values are expressed below: 1. Prioritize Patients - Patients are at the center of everything we do. Every decision we make is grounded in the needs and best interests of the patients we serve. 2. Drive Innovation - We are committed to pursuing big, bold ideas. Taking risks, trying new approaches, and challenging the status quo are necessary to speed new discoveries. 3. Deliver Solutions - Taking on complicated challenges is what sets us apart. To deliver results, we must be decisive, take action, and act with urgency on behalf of the myeloma community. 4. Do It Together - We know that together, we are stronger. We work cross-functionally with the entire community to achieve our mission and are invested in the success of others. 5. Build Trust - We build trust-based relationships. We advocate for each and every myeloma patient by committing to , equity, and and treating others with respect., The role provides hands-on experience working with modern cloud infrastructure, biomedical data platforms, and emerging AI-assisted research tools within a mission-driven nonprofit research environment. The will also have the opportunity to work with large-scale multi-omic datasets and modern open-source data platform technologies used by leading biomedical research institutions. The will work within a highly collaborative environment involving software engineers, computational scientists, and translational researchers supporting one of the largest data resources in multiple myeloma research. Where appropriate, contributions from the may contribute to scientific outputs such as conference abstracts, technical reports, and collaborative publications associated with the Virtual Lab platform. The is designed to provide structured mentorship and exposure to real-world scientific data infrastructure development while enabling the to contribute meaningfully to the MMRF's mission-driven research initiatives. Project Description: The Multiple Myeloma Research Foundation (MMRF) is developing an AI-powered research copilot within the MMRF Virtual Lab platform (virtuallab.themmrf.org) to support intuitive exploration of large-scale patient-derived clinical and multi-omic cancer datasets through natural interaction and AI-assisted analytical workflows. Built on the Gen3 data commons framework and deployed within AWS cloud infrastructure, Virtual Lab enables secure exploration and analysis of genomic, bulk & single-cell transcriptomic, methylation, and clinical outcome datasets generated from multiple myeloma patient cohorts. The project will focus on prototyping an AI-assisted research interface capable of translating natural research questions into structured data exploration and analytical tasks within the platform. Working alongside the MMRF Translational Research team and partners, the will explore integration of large models (LLMs), retrieval-augmented (RAG), platform APIs, and cloud- analytical workflows to support dynamic cohort discovery, exploratory visualization , and AI-assisted interrogation of translational research datasets. By the conclusion of the , the candidate is expected to deliver a prototype AI-assisted research interface demonstrating natural -driven exploratory analysis capabilities within the MMRF Virtual Lab platform, together with technical documentation and a final presentation to the Translational Research department.