304 machine-learning-"https:"-"https:"-"https:"-"https:"-"https:"-"University-of-Latvia" positions in Hong Kong
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. More information about the Faculty can be found at https://web.edu.hku.hk/ . The Position We now invite applications for appointment as Professor/Associate Professor/Assistant Professor in Learning
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to staff position within a Research Infrastructure? No Offer Description Ref.: 534447 Work type: Full-time Department: Teaching and Learning Innovation Centre (47500) Categories: Teaching Staff
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representation for multi-model fusion”. Qualifications Applicants for the Postdoctoral Fellow post should have a PhD degree in Computer Science, Electrical and Computer Engineering or a related discipline or an
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integration; (b) conduct algorithm research and development in areas such as computer vision, multimodal learning and embodied AI; (c) conduct experiments, data collection and performance evaluation; (d
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more than five years of post-qualification experience at the time of application; and (b) strong background in accounting, finance or computer science/natural language processing/machine learning
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) perform information updates and maintenance of accounts for the e-learning system; (c) conduct housekeeping in classrooms and laboratories; (d) assist in the setting up, operation and maintenance
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self-driven, highly motivated, creative with excellent communication skills in written and spoken English and Cantonese. Expertise and knowledge in AI deep learning model development on histology whole
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of further appointment] Duties The appointees will assist the project leader in the research project - “Multilingual speech brain-machine interface (BMI): accurately translating brain activity signal
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, finance or computing science/natural language processing/machine learning. Preference will be given to those who are proficient in Python, adept at processing large-scale data and have worked with large
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, machine learning systems, model merging/fusion or related areas; (b) strong self-directed learning ability; and (c) commitment to open, reproducible and ethically responsible AI research. Applicants