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Field
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Associate/Research Fellow with expertise in Artificial Intelligence (AI)/Machine Learning (ML), pedagogical research in Institutes of Higher Learning (IHLs), and web/mobile application development (both
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machine learning. Supervision will be provided by Prof. Ali Mazaheri, as well as Prof. Fang Gao Smith, and Prof. Helen McGettrick. The successful candidate will have a strong background in psychology
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Integrated Planning & Learning and Reinforcement Learning in non-deterministic and partially-observed scenarios. The methods will be evaluated on physical robots. The ideal candidate would have: A PhD (or
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-driven models to optimize solvent systems. Mentoring the training and learning of PhD and undergraduate students on sustainable biomass conversion topics Assist in report/document/further grant writing
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smart cities. To be successful you will have: PhD in Computer Science, Data Science, Machine Learning, Electrical Engineering, or a related field with focus on speech processing, edge computing, TinyML
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quantitative and digital methods, such as descriptive/inferential statistics, data modelling, machine learning (ML), experimental prototyping and technology ideation. A significant degree of autonomy is required
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record of publications in reputable peer-reviewed journals or conferences in maritime transport, logistics management, machine learning, deep learning, and optimization; Proficient in written and spoken
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computing language. Experience with machine learning methods is a plus. The research fellow must take part in the faculty’s approved PhD program and is expected to complete the project within the set
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”. Qualifications Applicants should: (a) have a PhD degree in Remote Sensing, Geomatics, GIS, Computer Science, Photogrammetry or a related field, and must have no more than five years of post-qualification
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neuroimaging and fluid biomarkers, (b) systems biology analysis of pathways from multi-omics data using multi-layered network approaches, © machine learning for identification of genetic risk factors in ADRD, (d