The proposed Taiwan Experience Education Program (TEEP) offers a comprehensive 3–6 month research and training opportunity focused on sustainable hydrogen production through water splitting. Hosted by the Department of Materials Science and Engineering at National Taipei University of Technology (Taipei Tech), the program integrates experimental materials science with machine learning–based data analysis.

Participants will receive hands-on training in the synthesis and characterization of advanced two-dimensional (2D) nanomaterials, including Metal–Organic Frameworks (MOFs), Layered Double Hydroxides (LDHs), hexagonal boron nitride (h-BN), and transition metal oxides. The program also includes electrochemical evaluation of catalysts for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER), followed by machine learning techniques to predict and optimize catalytic performance.

Duration and Schedule:

The program duration ranges from a minimum of 3 months to a maximum of 6 months, combining laboratory research, academic instruction, and optional industry-oriented internship components.

Financial Support and Costs:

Each participant will receive a monthly subsidy of NT$15,000, which includes:

NT$12,000 as a student stipend to support accommodation, daily expenses, and local transportation

NT$3,000 allocated for laboratory and research-related supplies

Accommodation:

Students are expected to arrange their own accommodation; however, guidance and support will be provided by the host institution to assist in finding suitable and affordable housing near the campus.

Participation Requirements:

Applicants should have a background in materials science, chemistry, chemical engineering, physics, or related disciplines. Basic knowledge of electrochemistry or nanomaterials is preferred. Participants should be proficient in English to effectively engage in research discussions and training activities.

Additional Considerations:

The program emphasizes interdisciplinary learning, international collaboration, and practical research experience. Participants are expected to actively engage in laboratory work, data analysis, and group discussions, with opportunities to contribute to joint publications or conference presentations.