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will work closely with the Principal Investigator (PI), Co-PI, and the research team to develop deep learning-based computer vision algorithms and software for object detection, classification, and
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research that addresses complex health and social care challenges of the 21st century. We employ traditional statistical and epidemiological methods, cutting-edge artificial intelligence algorithms, and
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, implementing, and optimising advanced AI algorithms, with deep proficiency in machine learning architectures, scalable model development, and high-performance code. The role holder will have the opportunity
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research that addresses complex health and social care challenges of the 21st century. We employ traditional statistical and epidemiological methods, cutting-edge artificial intelligence algorithms, and
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well as competence in mathematics including probability, statistics and algorithms. Keen interest to support research and academic project work, with demonstrated ability in developing software solutions to technical
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Inverse Methods and Ionospheric Modelling Research Fellow - School of Engineering - 106995 - Grade 7
, international collaboration, and data crawling Develop algorithms to process and clean large and diverse ionospheric datasets. Share research findings through publications, research seminars, etc. Guide and
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. This longitudinal project investigates the implementation of AI-empowered chronic disease management systems in hospitals. It examines human-AI collaboration and the "boundaries of work" between humans and algorithms