44 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" positions in Hong Kong
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are seeking an experienced and highly skilled Data Scientist with a strong foundation in genomic biostatistics to join our team. This role involves leveraging advanced statistical methods and machine learning
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at the rank of Research Assistant Professor in applied probability, data science, machine learning, and spatial statistics. Candidates with a strong background in the development of novel models and original
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English and Chinese Able to work independently and in a multidisciplinary team Experience in image analysis packages such as Freesurfer, FSL, SPM, or 3DSlicer, or using machine learning or artificial
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image analysis packages such as Freesurfer, FSL, SPM, or 3DSlicer, or using machine learning or artificial intelligence models would be advantageous What We Offer The appointee would be exposed to ample
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transforming into a hub for global leaders to develop and promote human-centric technology and social policies. Further information about Lingnan University is available at https://www.ln.edu.hk/ . Applications
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research areas, preferably demonstrated by publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential
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publications in high-impact venues. Experience with machine learning frameworks (e.g., PyTorch, JAX) and / or computational materials methods is essential. Additionally, the candidate should possess an excellent
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the importance attached to the socio-cultural environment of the Chinese and English languages. The appointee will be required to teach courses in some of the following areas: Computer-aided Translation
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. Interdisciplinary research is actively promoted by the Faculty of Science, fostered under the University-wide six Interdisciplinary Labs (https://interdisciplinary-research.hkbu.edu.hk/), and supported by state
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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