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Overview Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and
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on developing innovative algorithms and models to address complex problems in diverse fields such as robotics, healthcare, and finance. The department offers a range of undergraduate and graduate programs
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: Course number and title: MIE1624F/S – Introduction to Data Science and Analytics Course description: The objective of the course is to learn analytical models and overview quantitative algorithms
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Leader, Senior Research Scientists and Engineers, this Research Scientist will: Conduct innovative research in quantum software platforms, focusing on quantum compilers, algorithms, and hardware-agnostic
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range of computing subjects, including Cyber Security, Programming, Algorithms, Computer Logic and Architecture, Software Engineering, Database Design, both at undergraduate and postgraduate level
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. Knowledge or experience of Robot Operating System (ROS), tools for training and using deep learning algorithms and in image processing and computer vision algorithms and solutions using open-source software
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, and the ability to thrive in a highly cross-functional environment. They will primarily be responsible for the development of algorithms and pipelines to analyze vast amounts of electronic health
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algorithms and data structures. Experience with AI frameworks and libraries (e.g., TensorFlow, PyTorch). Ability to develop and implement AI models for business applications. Knowledge of cloud computing
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and implements dynamic models, including machine learning algorithms, to optimize student-centered outcomes. Creates clear and actionable visualizations and dashboards using tools such as Power BI
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both fundamental and applied research, from the development of algorithms, tools, and frameworks that advance scientific discovery to methodologies that utilize computational approaches to generate