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and materials to cater for the learning diversity of multicultural students; promoting learning and teaching (L&T) with assessment data; sharing school-based experience and good practices at teacher
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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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machine‑learning and deep‑learning frameworks for pathogen detection, drug‑target identification, antimicrobial discovery and protein‑protein interaction characterisation. Working familiarity with
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metabolomics datasets. Candidates should be experienced in molecular docking and virtual‑screening pipelines, alongside machine‑learning and deep‑learning frameworks for pathogen detection, drug‑target
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- “Experimental investigation into the mechanisms of plasma-assisted combustion for green liquid propellants”. Qualifications Applicants should have: (a) a doctoral degree, preferably in machine learning‑driven
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the project - “Engaging with diversity”. They will be required to: (a) coordinate service learning activities with students and collaborating agencies; (b) provide administrative support; (c) assist
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have: (a) an honours degree in Biomechanical Engineering, Apparel and Textile Design Technology, Machine Learning, Data Science or related disciplines or an equivalent qualification; and (b) good
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should: (a) have a good honours degree or an equivalent qualification; (b) have a good command of both written and spoken English and Chinese; (c) be proficient in Python and with the main machine
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Computer Science, Artificial Intelligence, Data Science Engineering or a related discipline; (b) demonstrated expertise in foundation models, generative AI, multimodal learning, machine learning systems, model
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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