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Field
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implementing RF signal processing algorithms on edge processors including RF System-on-a-Chip (RFSoC) devices with applications in radar and/or signal intelligence. Responsibilities and Essential Duties 1
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econometric analysis and preparing results tables, managing large data sets, handling spatial data, applying machine learning algorithms, conducting computationally intensive statistical analyses, summarizing
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the total compensation value with benefits. Qualifications Experience developing software to take practical advantage of state-of-the-art ML algorithms and research results in AI. (Required) Experience
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contributing to our clinical NLP tools, algorithms and interfaces used by clinical specialists. The post holder will be expected to contribute to: Extend our software platforms for electronic healthcare record
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research across diverse basic and applied science and engineering domains. Responsibilities will include: ● Design, develop, and deploy ML/DL algorithms for domain science and engineering fields ● Support
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learning including reinforcement learning, nature inspired algorithms, deep learning, agent based modeling, and natural language processing. We are specifically interested in research focused
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-resource settings. This project aims to achieve several objectives, including the development of a new AI-algorithm and a paired dataset for comparing how different imaging techniques influence
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communication systems for 5G and 6G, channel modelling, channel characterization, radio-based positioning and sensing, and associated signal processing algorithms. Work duties Employment as an assistant professor
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of Biomedical Engineering, please visit https://www.bme.ubc.ca/ . HuMBL, a research lab within the SBME, specializes specifically in wearable sensor technologies and algorithm-driven health analytics to enhance
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candidates whose work lies at the intersection of statistics, machine learning, data analytics and modern AI algorithms. This includes, in particular, statistics for high-dimensional and complex data