Scientific AI Intern
3 weeks ago
Role Overview
We seek a highly motivated Scientific AI Intern to develop AI-driven scientific computing applications in the domains of drug discovery, materials discovery, and quantum computing. You will work with scientific LLMs/FMs, gen AI, RAG, multi-agent systems, machine learning, and AI automation for scientific workflows and self-driving labs. You will support the research teams as well as product development teams in the QpiAI Quantum Software division.
Key Responsibilities
Build agentic AI for scientific workflow automation
Design multi-agent AI systems for autonomous cross-domain scientific discovery
Develop LLM-first scientific discovery applications with gen AI interfaces
Implement RAG/KGs for scientific data mining with scientific prompting
Build with GNNs, energy-based models, and thermodynamic computing
Help build task/application-specific AI workflows in computational chemistry
Collaborate with quantum computing, AI, HPC, and computational chemistry teams
Tailor scientific foundation models/LLMs for drug discovery, materials discovery
Build systems for end-to-end self-driving labs
Qualifications
PhD/MS in CS, AI, ML, QC, Computational Sciences, or Physical Sciences
Familiarity with gen AI, agentic AI, quantum computing, scientific computing, HPC
Proficient in Python, C/C++, CUDA, and exposure to Julia, Rust
Proficient in PyTorch, DGL, JAX, Dask, MPI4py, CuPy, Ray, MLFlow
Exposure to HuggingFace, LangChain, LlamaIndex, OpenAI APIs, AutoGen
Exposure to open-source quantum computing libraries is a big plus
Exposure to Kubernetes, Docker, Flyte is a big plus
Benefits: Gain hands-on experience with cutting-edge AI, HPC, and quantum technologies for scientific discovery in a collaborative, growth-oriented environment. Access to professional development resources and the potential for future full-time roles.
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