Meets at least one of the following criteria: Familiar with quantum chemistry algorithms, with experience in developing or using DFT/Post-HF computational tools or algorithmsFamiliar with molecular dynamics engine development, with experience modifying the source code of LAMMPS or OpenMMFamiliar with machine learning algorithms, with hands-on experience in at least one of the following areas: LLMs, reinforcement learning, agents, or generative modelsFamiliar with solid-state physics, with hands-on experience in materials simulation and MLIP developmentFamiliar with statistical mechanics and enhanced sampling algorithms, with strong domain knowledge and development capability. About the Team: The AI for Science team has been focusing on tackling challenges in natural sciences, including biology, physics, and materials, with computational tools such as Machine Learning, Computational Chemistry, High-throughput Computation.