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EmailGitHubHost Lab
PRINCIPAL CONTACTZe Liu · Associate Professorliuze@ouc.edu.cn
Key Lab of Submarine Geosciences and Prospecting Techniques, MOE ↗
Ocean University of China
238 Songling Road, Laoshan District
Qingdao 266100, Shandong, P.R. China
Research recruitment

Study the Earth with intelligence.

We welcome senior undergraduates, master’s students, and PhD students who want to explore the next generation of AI × ocean geology × Earth science research.

01 · Senior undergraduates

Start with a real scientific question.

Build sustained research experience beyond a practice project, with clear questions, experiments, and research outputs.

02 · Master’s students

Develop depth across disciplines.

Connect AI methods, scientific computing, and domain knowledge through a complete research workflow.

03 · PhD students

Push an ambitious direction forward.

Develop AI-native research tools and scientific discoveries around challenging Earth-system questions.

Backgrounds we welcome

Artificial intelligence · Computer science · Software engineering · Geophysics · Geology · Ocean science · Mathematics · Physics · Mechanics · Ecology · Biology · Geographic information science · Earth system science

You do not need to know everything at the start. Curiosity, sustained progress, and a willingness to learn matter most.
What we look for

A strong foundation for research growth.

  • Interest in AI, scientific computing, ocean geology, or Earth science.
  • A working foundation in Python programming.
  • Willingness to learn knowledge from emerging interdisciplinary fields.
  • Capacity to commit consistent time to research training.
  • Ability to learn independently, read literature, run experiments, or contribute to scientific writing.
Bonus experience

Useful skills—not prerequisites.

  • PyTorch or TensorFlow.
  • Transformers, PINNs, neural operators, or LLM agents.
  • Geophysics, ocean geology, structural geology, or ecological data analysis.
  • Research papers, competitions, open-source projects, or a GitHub portfolio.
  • GMT, PyGMT, PyVista, xarray, NetCDF, or GIS tools.
  • Finite elements, finite differences, HPC, or Docker.
What you will gain

Research training from question to publication.

  • Opportunities to participate in frontier AI for Science research projects.
  • End-to-end training in problem decomposition, model design, experimental analysis, and scientific writing.
  • Guidance from the supervisor and team on research ideas, technical routes, and writing.
  • Opportunities to contribute to papers, patents, and open-source projects, with clear authorship based on individual contributions.
  • Strong contributors may join SCI papers, academic conferences, or follow-on research projects.
  • Research reward support of approximately ¥2,000–6,000, depending on completion, team contribution, and project arrangements.
  • Access to CPU/GPU computing, domestic and international foundation models, research accounts, data resources, and the team GitHub platform.
How to apply

Tell us what you want to explore.

If you want to contribute to a real exploration of future AI-native science—not only a practice project—we would like to hear from you.

Email kunlinghire@126.com and CC liuze@ouc.edu.cn with:

  1. 01Your CV or résumé.
  2. 02Your university, year of study, and major.
  3. 03The project direction that interests you.
  4. 04Relevant code, papers, competitions, course projects, or GitHub work.
  5. 05Your estimated weekly time commitment.
Apply by email →