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of areas, including AI and machine learning, cloud and mobile computing, computer system and information security, evolutionary computation, computer vision and graphics, and bioinformatics
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in their learning; (c) organise activities for students to enrich their learning experience; and (d) perform any other duties as assigned by the Project Leader or his/her delegates
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machine learning-enhanced algorithm incorporating domain knowledge for sustainable maritime transport”. Qualifications Applicants should have: (a) an honours degree, preferably in mathematics, logistics
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- “Towards digital biomanufacturing – developing physics-informed machine learning framework for the advanced multi-modular 3D bioprinting system”. Qualifications Applicants should have: (a) a doctoral
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quantitative and analytical skills; (c) in-depth experience in econometric modelling and modern machine learning techniques; and (d) strong proficiency in handling large-scale datasets and advanced
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intelligence (AI)-assisted image analysis for bioinformatics and medicine. The project is highly interdisciplinary, involving areas of microfluidics, fluidic mechanics, biomedical imaging, and machine learning
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quality assessment filters and standardise data augmentation. Machine Learning Model Development and Analysis Train and benchmark unimodal (image-only) and multimodal (image + questionnaire) models (e.g
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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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faculty positions on tenure-track. Assistant Professor (Computer Science) (25260312) The appointees will perform high-impact research, teach and supervise students at undergraduate and postgraduate levels
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years of post-qualification experience at the time of application; (b) experience in using machine learning for research projects; and (c) have a good command of both written and spoken English