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- CITY UNIVERSITY OF MACAU
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Resonance Imaging (MRI). This post also be linked to research activities linked to the University’s research platforms such as the UNNC Sir Peter Mansfield MRI Centre. Candidates must have a PhD degree in the
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Project title Multi-Modal Large Language Model for Medical Image Analysis Research period 2 years Abstract The proposed research project aims to develop a novel multi-modal large language model (MLLM
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initiatives Cutting-edge research in: AI-driven medical imaging & data analytics Smart healthcare for aging populations Biomedical sensors & intelligent diagnostics Ion channel-targeted drug development Impact
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Intelligence (including AI for Science/Math) 3.Data Science 4.Computational Mathematics, and Computational Imaging 5.Mathematical Modeling with Interdisciplinary Applications Qualifications: Ph.D. in Mathematics
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Diseases, (4) Biomedical Imaging, (5) Data Science, (6) Drug Development, (7) Neuropsychiatry, (8) Structural Biology, (9) Translational Medicine, and (10) Public Health. Initial appointment is up to 12
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, and VR and AR. Experience and practice in the industry, sound design, and creative coding are desirable skills that we could use. The successful candidate will be responsible for maintaining a creative
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medicine, biomedical electronics, medical robotics, sensors, instrumentation, brain-computer interface, intra-body communications, and medical imaging. More details about the department are available from
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of atomically precise building blocks and advanced materials (3) Atomic scale electronic devices: prototype devices design and advanced processing technology. These areas aim to explore development from atomic
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tackle global challenges. such as quantum technologies, advanced imaging, and innovations in materials science. The department is involved in the delivery of undergraduate physics and mathematics modules
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mathematics (Pure Mathematics: Analysis, Algebra, Geometry and Topology, Algebraic Geometry, etc. Applied Mathematics: Information Theory, Coding and Cryptography, Mathematical Foundations of Signal Processing