Note: The job is a remote job and is open to candidates in USA. The Multiple Myeloma Research Foundation (MMRF) is the largest nonprofit focused on accelerating a cure for multiple myeloma patients. The AI Research Engineering Intern will support the introduction of AI applications to the Virtual Lab platform, working with a team to enhance the platform and prototype new analytical capabilities.

Responsibilities

• Engage with a project supporting the introduction of AI applications to the Virtual Lab platform
• 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
• Provide hands-on experience working with modern cloud infrastructure, biomedical data platforms, and emerging AI-assisted research tools within a mission-driven nonprofit research environment
• Work with large-scale multi-omic datasets and modern open-source data platform technologies used by leading biomedical research institutions
• Contribute to scientific outputs such as conference abstracts, technical reports, and collaborative publications associated with the Virtual Lab platform
• Deliver a prototype AI-assisted research interface demonstrating natural language-driven exploratory analysis capabilities within the MMRF Virtual Lab platform, together with technical documentation and a final presentation to the Translational Research department

Skills

• 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 language, 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

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