Machine Learning Research Scientist Intern (Seed AI for Science - Atomistic AI) - 2027 Start (PhD)

About the Team

The AI for Science team focuses on tackling challenges in natural sciences, including biology, physics, and materials, with computational tools such as Machine Learning, Computational Chemistry, and High-throughput Computation. Our goal is to create breakthroughs in natural science with new methodology and help the world. PhD internships provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies. The internship blends hands-on learning, community-building, professional development events, and collaboration with industry experts.

Responsibilities

• Track cutting-edge research developments across the industry and work closely with the team to build deep and broad technical understanding of the field.
• Integrate methods from multiple disciplines, including machine learning, quantum chemistry, and molecular dynamics, to explore frontier applications in biology and materials science.
• Consolidate research outcomes from both the industry and internal teams, and help translate research into practical applications with broad impact.

Qualifications

Minimum Qualifications:

• Currently pursuing a Ph.D.; preferred majors include Computer Science, Mathematics, Physics, Computational Materials Science, Quantum Chemistry, or related fields.
• Strong communication and teamwork skills, a proactive willingness to learn, and a conscientious, responsible work ethic.
• Proficiency in at least one programming language, such as Python, C, C++, CUDA, or Triton, with solid engineering capability and the ability to effectively orchestrate coding agents in development workflows.
• 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 algorithms;
  • Familiar with molecular dynamics engine development, with experience modifying the source code of LAMMPS or OpenMM;
  • Familiar with machine learning algorithms, with hands-on experience in at least one of the following areas: LLMs, reinforcement learning, agents, or generative models;
  • Familiar with solid-state physics, with hands-on experience in materials simulation and MLIP development;
  • Familiar with statistical mechanics and enhanced sampling algorithms, with strong domain knowledge and development capability.

Candidates with publications in top journals in related fields and/or strong industry experience will be preferred.

Pay

The hourly rate range for this position is $57-$57.

Benefits

• Day one access to health insurance, life insurance, and wellbeing benefits.
• 10 paid holidays per year and paid sick time (56 hours if hired in the first half of the year, 40 if hired in the second half).
• Eligibility for housing allowance if not working 100% remote.

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.