Research Scientist Graduate (AML - AI-for-Science) - 2025 Start (PhD)

$106,590 - $139,650/Yr

Bytedance - Seattle, WA

Full-time - Entry Level

Seattle, WA

Professional, Scientific, and Technical Services

About the position

ByteDance is seeking a Research Scientist Graduate for the AI-for-Science team, focusing on applying machine learning and computational tools to tackle challenges in natural sciences such as biology, physics, and materials. This position is set to start in 2025, and successful candidates will have the opportunity to work on groundbreaking methodologies that aim to create breakthroughs in natural science. The role involves solving real-world problems by combining machine learning methods with high-performance computing approaches, including molecular dynamics and quantum chemistry. As a graduate, you will be part of a team that values creativity and innovation, and you will be encouraged to pursue bold ideas and explore limitless growth opportunities within the company. The AI for Science team is dedicated to using advanced computational techniques to enhance our understanding of complex biological systems and materials. You will be expected to stay updated on the latest advancements in the field and apply your knowledge to real-world applications. The ideal candidate will possess a strong foundation in machine learning, particularly in areas such as reinforcement learning, and will have hands-on experience with tools like Python and PyTorch. This position offers a unique chance to contribute to significant scientific advancements while being part of a collaborative and dynamic team environment.

Responsibilities

• Follow the latest progress and solve real-world problems in biology, combining machine learning methods and high-performance computing approaches such as molecular dynamics and quantum chemistry.

Requirements

• Proficiency in Python and PyTorch
• Solid coding skills
• Hands-on experience with machine learning algorithms, such as graph neural networks, generative models, and reinforcement learning
• Deep domain knowledge in protein, DNA/RNA, and general organic molecules
• Ability to solve problems independently
• Good teamwork and communication skills

Nice-to-haves

• Experience with molecular dynamics and enhanced sampling algorithms
• Experience in protein and bio-molecule modeling
• Experience with quantum chemistry density functional theory algorithms
• Experience in generative modeling of organic molecules