Research Scientist Intern; Seed - Generative AI Science PhD

Position: Research Scientist Intern (Seed - Generative AI for Science) - 2026 Start (PhD)
About the Team:
Our team at Byte Dance Seed has been focusing on building foundation models for science, including biology, physics, and chemistry. We are looking for outstanding researchers to join our team and conduct cutting-edge research in AI for Science. We are looking for talented individuals to join us for an internship in 2026. PhD Internships at Byte Dance aim to provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies.

PhD internships at Byte Dance provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and development events, and collaboration with industry experts. Applications will be reviewed on a rolling basis - we encourage you to apply early. Please state your availability clearly in your resume (Start date, End date).

Responsibilities:

- Develop foundation models for nature science, such as protein structure prediction, molecular conformation analysis, and computational protein design;

- Replicate and assess emerging AI/ML methods using public benchmarks and databases;

- Collaborate closely with the multidisciplinary drug discovery team, applying inventive algorithms to cutting-edge challenges;

- Stay updated with the latest scientific literature;

- Communicate and elucidate computational models and AI techniques to a diverse audience spanning multiple disciplines.

Minimum Qualifications:

- Currently Pursuing a Ph.D. in fields like computer science, electrical computer engineering, or related areas.

- Strong research background in AI and machine learning with solid publications in leading conferences (e.g., ICML, NeurIPS, ICLR) and journals, encompassing areas like large language models, diffusion models, geometric deep learning, natural language processing, computational protein design, protein structure and conformation prediction, and related fields.

- Proficient in Python programming and deep learning platforms, such as Pytorch. By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: