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data sources such as UK Biobank and eventually come up with algorithm useable for the early detection of Alzheimer’s disease (AD) and Parkinson’s disease (PD). Nature of Work: In this project, we will
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Science Specialist will: 1) review empirical data and algorithms applied to the price, end-use, fishing effort and layer 3 databases and develop code that imputes missing data to complete gaps in
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developing machine learning algorithms specifically designed for medical imaging applications. In addition, performs analysis of tissue images of cancer using machine learning methods that have been prototyped
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on Wednesdays and Fridays 11:35-12:55 and labs Mondays 15:35-17:25. This course includes an Introduction to problem-solving methods and algorithm development. Emphasis is on designing, coding, debugging, and
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Dalhousie University | Halifax Mid Harbour Nova Scotia Provincial Government, Nova Scotia | Canada | about 18 hours ago
Computer Engineering Fundamentals Algorithms for Computer Engineers Microprocessors Operating Systems Real-Time Systems Computer Security Electrical and Computer Engineering Design Engineering Design II
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on Wednesdays and Fridays 11:35-12:55 and labs Mondays 15:35-17:25. This course includes an Introduction to problem-solving methods and algorithm development. Emphasis is on designing, coding, debugging, and
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technical subjects such as programming, data science, machine learning, and algorithmic fairness is highly desirable. Candidates must have teaching experience in a degree-granting program, including lecture
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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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signal processing algorithms on FPGA, optimized to significantly improve the resolution of real-time energy measurements made by the ATLAS Liquid Argon Calorimeter system. Use novel high-level synthesis
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, Python, or C/C++, with the ability to develop custom scripts and algorithms for data analysis and modeling. Familiarity with rheological characterization techniques, such as rheometry or viscometry