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Medical School. In August 2024, we welcomed our first intake of the NTU MBBS programme, that has been recently enhanced to include themes like precision medicine and Artificial Intelligence (AI) in
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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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expertise in biostatistics, bioinformatics, or computational biology. The successful candidate will join a dynamic and interdisciplinary team focusing on the development and application of novel statistical
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timely and quality deliverables. Co-supervision of MSc and Final Year Project students involved in this project. Job Requirements: Bachelor/Master/PhD in Electrical and Electronic Engineering/Computer
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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, including machine learning, computer vision, adaptive data modelling, and computational imaging. The objective is to develop state-of-the-art machine learning algorithms for solving ill-posed inverse problems
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to the applications of mathematics in cryptography, computing, business, and finance. PAP covers many areas of fundamental and applied physics, including quantum information, condensed matter physics, biophysics, and
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equivalent) in Geospatial Sciences, Computer Sciences, Architecture and Urban Planning, Environmental Sciences, Geography, Landscape Ecology, or any other related field. • Strong research background in
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with a team, have an investigative nature and attention to detail; have knowledge of computer applications (such as SPSS and MS Office, PowerPoint); and have good communication skills with patients and
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-bed and facilitate large-scale, community-based service innovations through a variety of methods including programme evaluation and social analytics. The Research Fellow will join a dynamic multi