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LOCATION Downtown Campus TEACHING QUALIFICATION REQUIREMENTS : Experience Experience in the following area: Python programming; Algorithms; Software design; Applications
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Mount Allison University | Fredericton South New Brunswick Provincial Government, New Brunswick | Canada | 4 days ago
academic term, which are provisionally planned to be Programming Techniques and Algorithms (COMP 1731), which includes a weekly three-hour lab conducted in Java, and Algorithm Analysis (COMP 3611). Calendar
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: Technical Skills in the following categories are necessary: Strong background in image processing techniques. Experience with AI, machine learning and deep learning algorithms, particularly in computer vision
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required. Programming skills are not necessary, but experience in genomic research and a broad knowledge of methods and algorithms behind genomic resources is required (e.g. next-generation sequencing
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candidates with computational tools and machine learning algorithms, and elucidating structure-property relationships of emerging molecules, polymers, solid-state materials, formulations, etc. Tasks include
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telecommunications, radio and wireless systems is required. Knowledge of radio frequency propagation principles, antenna principles, telecommunications transmission media, telecommunications signals, design, analysis
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media, newsletters, and event promotion. Ability to research and adapt to evolving social media trends, algorithms, and digital marketing techniques. Experience creating and managing content calendars and
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: Course number and title: MIE1622H – Computational Finance and Risk Management Course description: The objective of the course is to examine the construction of computational algorithms in solving financial
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-based prediction. This includes instrumenting a high-power APS torch with video and acoustic sensors, developing machine learning algorithms for feature extraction, and building predictive models
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of developing algorithms that are both technically robust and clinically relevant, ensuring that these innovations can be integrated seamlessly into existing imaging systems and workflows. Collaborating with