ML Research Intern (Summer 2026) – PhD… at Genesis… · San Diego

Summary: Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. The successful candidate will work on building research infrastructure that connects AI agents to biomedical databases and develop intelligent workflows for drug discovery. Responsibilities: - Help build infrastructure that connects AI agents to public biomedical databases (e.g., Open Targets, UniProt, DepMap, PubChem, GWAS Catalog, etc) and enables intelligent tool selection and use - Design and prototype agentic workflows that chain data retrieval, analysis, and reasoning across heterogeneous sources to answer real drug discovery questions - Explore approaches for tool discovery, workflow composition, and validation that make the platform increasingly useful over time - Document architecture decisions and methodology; present your work to the research team Required Qualifications: - Currently enrolled in a graduate program in Computational Biology, Bioinformatics, Computer Science, or related field - A strong Python programmer - Familiarity with LLMs and an interest in agentic AI patterns (tool-use, function calling, multi-step reasoning) - Experience working with APIs (REST or GraphQL) and building structured data pipelines - Enough biological context to understand the scientific underpinnings of drug target identification and translational biology - Strong analytical and problem-solving skills Preferred Qualifications: - Scientific tool orchestration frameworks or custom agentic pipelines - MCP (Model Context Protocol) or similar tool-serving frameworks - Graph databases and knowledge graph construction - Graph neural networks, knowledge graph embeddings, or graph reasoning techniques - Working with large-scale public genomics platforms (DepMap, TCGA, CCLE, Open Targets, GWAS Catalog, etc) - Open-source software development practices (version control, testing, documentation) Required Skills: Python programming, Large language models (LLMs), Agentic AI patterns, API development REST, API development GraphQL, Structured data pipelines, Computational biology, Bioinformatics, Scientific tool orchestration frameworks, Model Context Protocol (MCP), Graph databases, Knowledge graph construction, Graph neural networks, Knowledge graph embeddings, Graph reasoning techniques, Public genomics platforms, Analytical skills Internship Start Date: Start in 2026 Summer