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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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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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/HSV/Lab), texture (GLCM, LBP), geometry, and other visual proxies for clinical assessment; and Build image quality assessment filters and standardise data augmentation. Machine Learning Model
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project – “Data augmentation and machine learning model evaluation for smart building services”. They will be required to: (a) assist in writing and programming the advanced AI Large Language Model
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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
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. Applicant(s) should possess a Ph.D. degree, or equivalent, in biological or computer sciences or a related discipline. Experience in any of the following fields, including 1) biological image acquisition
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of Computer Science has internationally known research groups in a number of areas, including AI and machine learning, cloud and mobile computing, computer system and information security, evolutionary computation
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VR-based tasks to study user cognition and creative performance; • process and analyse EEG data using advanced signal processing and machine learning techniques; • evaluate cognitive load
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, the appointee will help co-supervise MPhil and PhD students, establish a cutting-edge research programme in computational chemistry and machine learning, and engage in various scholarly activities, including