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Field
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learning algorithms focused on image data, natural language processing, and tabular data Conduct exploratory data analysis and feature engineering for high-dimensional datasets, including image, text, and
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, equipped with state-of-the-art facilities, to work on the following: Conduct research, development, and testing of SLAM and multi-sensor fusion algorithms for UAV swarms in GNSS-denied, cluttered
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, equipped with state-of-the-art facilities, to work on the following: Conduct research, development, and testing of SLAM and multi-sensor fusion algorithms for UAV swarms in GNSS-denied, cluttered
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generation of enhancement algorithms tailored for endoscopic videos, with a focus on applications in real-time interventions. Development efforts will prioritize both enhancement quality and computational
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talented and dedicated employees. Applies advanced computational, computer science, data science, and software research and development principles to perform complex distributed computing architectural
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of Public Health Minimum Position Qualifications Bachelor’s Degree in Information Systems, Computer Science or a relevant area and two (2) years of appropriate experience to include experience for web
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faculty in developing theory and application tools for artificial intelligence (AI), and training efficient data analytics. 60% - Leading research in AI will include generative models, algorithms and
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of PhD students on this project, collaborating with other partners in the ARIA programme, assisting with the delivery of project milestones, and managing the project’s codebase. We expect novel algorithms
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collection methods for external data (e.g. web scraping) to collect data for use in modelling and analysis. Develop analytic plans, engineer supporting algorithms, write new functions or applications in
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Applied Machine Learning: Knowledge of integrating machine learning models and algorithms into applications. • A knowledge of applied computer science and AI in software/app development and rapid prototype