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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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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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McGill University | Winnipeg Sargent Park Daniel McIntyre Inkster SE, Manitoba | Canada | 2 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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functional MRI analysis, EEG analysis, brain anatomy and connectivity. Advanced in: bio math/stats: biophysical modeling; multivariate techniques such as PLS, MDS; machine learning, signal processing
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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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curriculum standards and learning objectives. • Collaborate with faculty members and industry professionals to ensure course content is relevant and up to date. • Utilize various
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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