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, developing, and implementing innovative machine learning models and algorithms to drive insights from the hEDS*omics multimodal dataset, encompassing clinical, environmental, and multi-omics data. This role
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: Department of Bioresource Engineering Position Summary: Help with sensor maintenance, fabrication of new hardware components, data acquisition system development, field data collection, assistance to other
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learning algorithm for multi-omics integration 3) Maintenance of server / database (Linux environment) 4) Assisting other team members in data analytics 5) Presenting work in at least one conference in
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power of data science and algorithmic research with the fields of democratic theory, political science, and public policy. Ideally, the candidate has expertise and interest in innovative research using
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. Deployment and maintenance of eco-physiological instruments (e.g., chambers, sap flow sensors). Contribute to modeling and upscaling efforts using process-based and remote sensing-driven approaches. Support
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objective is to develop a next generation of AI approaches that are more sustainable and accessible. Relevant domains include mathematical and computational optimization, learning algorithms, statistical
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. The ultimate objective is to develop a next generation of AI approaches that are more sustainable and accessible. Relevant domains include mathematical and computational optimization, learning algorithms
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, and explainability; developing unbiased algorithms and responsible data use; addressing the social impacts of AI and IT-induced biases; equitable compensation policies; combating labour discrimination