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related to staff position within a Research Infrastructure? No Offer Description Ref.: 533859 Work type: Full-time Department: Department of Surgery, School of Clinical Medicine (21700) Categories
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- “Deep learning-based approach for process parameter optimization of SiC wafer under limited data”. He/She will carry out research in the area of machine learning (ML) and data science, and also be
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of ecological data and sustainability issues - Materials Science: AI-driven discovery and design of new materials Applicants should have (i) a Ph.D. in Computer Science, Computer Engineering, Electrical
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) for the requirements for application documents and other details. Application will be reviewed by a panel of scholars from across the spectrum of the arts and the humanities. The application process closes on February
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project - “Development of an intelligent process system for ring forging manufacturing based on AI deep machine learning”. Qualifications Applicants should have a doctoral degree plus substantial
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to inquiries from applicants regarding academic programmes and study pathways; (i) evaluate and report on student experiences to enhance onboarding processes; (j) recruit, train and supervise student
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assist the project leader in the research project - “Jockey club smart ageing hub”. He/She will be required to: (a) provide general support to the daily operation of the Day Experience Centre
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), Natural language processing and Social Network Analysis courses on modern computational social science methods at the graduate level; A track record of completed projects working with computational models
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Professors/Associate Professors/Assistant Professors, Department of Computer Science and Engineering
machine learning Bioinformatics Computer system security or cybersecurity Data analytics or data science Healthcare Informatics Image processing, computer graphics, AR/VR Programming languages, software
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of the arts and the humanities. The application process closes on February 28, 2026. Successful applicants will be notified by the end of April 2026. The University is committed to diversity and inclusivity