436 machine-learning "https:" "https:" "https:" "https:" "RAEGE Az" positions in China
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Jiaotong University, the continued development of the four new Academies, and exploring further potential locations to develop the SE model. With a focus on innovative learning, teaching, and research, XJTLU
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candidates with expertise in communications or photonics technologies; although excellent candidates in any research area with the ability to teach across a range of topics in our undergraduate curriculum will
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to curriculum development, ensuring innovative approaches to learning, teaching, and assessment that reflect international best practice. Lead and support major funding bids, develop partnerships with industry
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fostering an inclusive and high-performing academic community. Contribute to curriculum development, ensuring innovative approaches to learning, teaching, and assessment that reflect international best
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with the ability to teach across a range of topics in our undergraduate curriculum will be considered. It is required that the candidate has strong academic experience and evidence of strong track record
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in their fields. Please check https://sds.cuhk.edu.cn/en for more details. To apply, visit https://jobs.cuhk.edu.cn/jobDetails?id=313&channel=SDS3 and click the "APPLY NOW" button. Submit your cover
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cultural data. Experience with AI tools such as machine learning for sentiment analysis, data mining for social trends, or computational linguistics for linguistic analysis will be highly regarded
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Intelligence / AI/Machine Learning Particle Physics / Phenomenology , Phenomenology and Theory Appl Deadline: 2026/01/31 11:59PM (posted 2025/11/24, listed until 2026/05/24) Position Description: Apply
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Contact: School of Mathematical Sciences , +86 010 68903637 Postal Mail:105 North Xisanhuan Road, Beijing City，China Web Page: https://math.cnu.edu.cn/ We are not accepting applications for this job through
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record in academic quality assurance, curriculum design, assessment moderation, and governance. Experience implementing innovative pedagogies and driving continuous improvement in teaching and learning