We are looking for talented individuals to join our team in 2027. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company.
Successful candidates must be able to commit to an onboarding date by end of year 2027. Please state your availability and graduation date clearly in your resume.
Team Introduction:
The Seed-AI for Science team applies AI to drive breakthroughs in scientific computing research paradigms, focusing on biological foundation models, quantum chemistry, and molecular dynamics.
We are looking for candidates to join our team and conduct cutting-edge research in fundamental science, leveraging advanced machine learning techniques and large-scale computational infrastructure.
Topic Content:
Exploring research related to biomolecular design, quantum chemistry, multimodal large models for biomolecular structures, and machine learning-driven molecular dynamics.
- Biomolecular Design: Developing multimodal foundational large models for the natural sciences, applied to the design, conformation generation, and structure prediction of proteins, DNA, RNA, and other biomolecules.
- Quantum Chemistry: Conducting interdisciplinary research at the intersection of machine learning, quantum physics, and quantum chemistry to enable large-scale, high-precision scientific computing and numerical simulations.
- Multimodal Biomolecular Structure Large Models: Building structure-centric multimodal large models for biomolecules, using a unified architecture to support key tasks including complex structure prediction, functional modeling, and molecular design.
- Machine Learning Molecular Dynamics: Exploring the application of machine learning methods in force field development, molecular dynamics simulations, enhanced sampling, and other property calculation approaches, and scaling these for applications in drug discovery and materials discovery.
Responsibilities:
- Conduct interdisciplinary research at the intersection of machine learning and scientific computing, exploring applications of AI in scientific domains such as physics and chemistry.
- Develop large-scale numerical simulations for scientific computing, improving computational efficiency and accuracy.
- Collaborate with interdisciplinary teams to drive projects from research exploration to full engineering deployment.Minimum Qualifications:
- Individuals who are completing or have recently completed a PhD degree in Computer Science, Machine Learning, Physics, Chemistry, Mathematics, or related fields.
- Solid foundation in mathematics and strong programming skills.
- Demonstrated ability for independent research and innovation, with the capacity to thrive in a fast-paced, interdisciplinary environment.
- Strong interest in cutting-edge developments in artificial intelligence, with proficiency in using a wide range of AI tools.