17 python-"Prof"-"NTNU---Norwegian-University-of-Science-and-Technology" positions at Hong Kong Polytechnic University
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Python. Proven experience in Natural Language Processing and Language Models research (e.g. publications, projects) is preferred. Applicants are invited to contact Prof. Chersoni Emmanuele at telephone
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background in finance or accounting research; and (c) strong skills in Stata and Python. Applicants are invited to contact Prof. Chong Wang at telephone number 2766 4246 or via email at chong.wang
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proficient in Python and at least one deep learning framework (PyTorch/TensorFlow/JAX); (b) be familiar with distributed training frameworks such as Hugging Face Transformers, DeepSpeed and Megatron-LM; (c
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MAFA programme”. He/She will be required to: (a) help conducting the python summer bootcamp and the technology-related tutorials for the four technical subjects designed for MAFA; (b) prepare training
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Applicants should: (a) have an honours degree or an equivalent qualification; (b) be familiar with textual analysis techniques; (c) be proficient in Python programming; and (d) be capable
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computer science, maritime economic or a related field, preferably with a publication record in computer vision or maritime-related research; (b) proficiency in programming, including Python and Matlab, data
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robotics, localization, mapping, and multi-modal sensor fusion; (b) proficiency in programming languages such as Python and C++; (c) demonstrated ability to conduct independent research and contribute
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manual data coding or crawling from online platforms; and (c) assist in data analysis with Stata and Python, among other activities. Qualifications Applicants should: (a) have an honours degree
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computing with Python and R; (d) experience in high-performance and cloud computing for data processing; (e) the ability to work independently and collaboratively with an interdisciplinary research team
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using one of the software including STATA, Python, R, or Matlab; and (c) completion of undergraduate or post-graduate level courses in Statistics and/or Optimization with good grades. Preference will