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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
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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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: 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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, 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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Health Access Services This position will be responsible for performing essential tasks required for the creation and revision of Epic scheduling decision trees (algorithms) and for leading other Maestro
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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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with the regulatory environment around Deep Learning or Machine Learning algorithms Experience applying quality system standards, software development standards and regulation, e.g. ISO 13485, IEC 62304
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. Responsibilities Design, implement, and assess advanced underwater acoustic modeling techniques and algorithm development across various disciplines such as signal processing, statistical inference, propagation
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. Responsibilities Designing software applications and algorithms to support remote sensing, geospatial data analysis, and data science applications. Conducting software testing, code reviews, CI/CD, and verification