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Position Description The Institute of Natural Sciences (INS, https://ins.sjtu.edu.cn/ ), Shanghai Jiao Tong University, is an interdisciplinary platform for conducting first-rate research, education
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teaching practices, active learning, inclusive pedagogy, and project-based or experiential approaches to education. Evidence of engagement with teaching innovation, curriculum development, or the scholarship
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Job Responsibilities The successful candidate will be expected to: Teach and
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are affiliated with at least one of the professional accounting bodies as follows: AICPA, UK CIMA/ICAEW/ACCA, CA/CPA Australia, CICPA/HKICPA. Members of the department mainly teach BA Accounting programme and MSc
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given to candidates who can undertake independent research leading to outstanding outcomes or have extensive working experience. The new faculty member is expected to teach some of the following courses
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. Outstanding applicants will be recommended for the prestigious “Shuimu Tsinghua Scholar” Fellowship (https://postdoctor.tsinghua.edu.cn/info/zxtz/2174 ) or equivalent talent programs. We offer internationally
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of the People’s Republic of China and international passport holders. XJTLU offers our undergraduates and postgraduates over 100 programmes with a diverse spectrum of courses. With a focus on innovative learning
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assessments. You will be part of a small team of staff responsible for the delivery of the Bachelor of Design. We have an opportunity for a dedicated and motivated educator to teach computing at the Joint
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applications from candidates interested in interdisciplinarity and collaboration within the Department and School. Please see https://www.xjtlu.edu.cn/en/study/departments/academic-departments/department
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, scikit-learn, PyTorch, TensorFlow); additional experience with R, MATLAB, or Julia is an advantage. Machine Learning Expertise: Familiarity with causal machine learning, ensemble methods, and deep learning