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summarizing research interests, relevant experience and availability, and sample code or links to repositories (GitHub, GitLab, etc.) demonstrating Unity, C++, C#, or AR work (optional but preferred). Review
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demonstrate a strong sense of responsibility and have a good command of written and spoken English. The ideal applicant is self-motivated, detail-oriented, and capable of managing multiple tasks. Good
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independently and in a team. Priority will be given to those who have solid research experience in the field of education. The appointee will assist the Lead Researcher to conduct landscape research and multiple
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, code generation, agent development, multimodal AI applications, or related technologies. How to Apply Applications are accepted exclusively online. Applicants should submit their application via
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development is a strong plus (e.g., domain-specific agents, RAG, code generation, or practical applications); Experience in grant proposal preparation; and Proven experience in research project management