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initiatives, or with programming language experience and experience in machine learning and health informatics. An understanding of the digital health space, is expected but not essential. Must have previously
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spatial omics datasets. The position will also contribute to multi-modal data integration efforts that combine imaging, genomics, and machine learning approaches. Key Responsibilities Data Processing
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approaches (based on functional programming abstractions) to optimize the implementation of machine learning models and other digital signal processing algorithms on a specific FPGA architecture to fit within
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Science, or a related field. Strong programming skills in Python, R, or related languages for data analysis and machine learning. Experience with genomics data analysis, health informatics, or computational
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at McGill University), do not apply through this Career Site. Login to your McGill Workday account and apply to this posting using the Find Jobs report (type Find Jobs in the search bar). To teach visual
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McGill University | Winnipeg Sargent Park Daniel McIntyre Inkster SE, Manitoba | Canada | 3 months ago
fluorescence data. Developing machine learning methods to optimize data collection. In addition, the project is committed to developing open source tools that benefit the imaging community. The applicant will
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datasets, including time-series analysis and machine learning applications. Use spatial statistical tools to relate remote sensing and in-situ observations. Proficiency in geospatial software platforms
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data analytic approaches such as artificial intelligence (AI) and machine-learning to address this complexity are of particular interest. McGill University has an international reputation in excellence
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: - To lead the computational part of a collaborative project on AI-assisted design of OPVs - To become knowledgeable in the field of OPVs and the relevant simulations - To learn relevant machine learning