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dynamism. Its status as a comprehensive university allows for multidisciplinary learning and teaching and has great potential for internationally renowned, interdisciplinary research. Almost all of its
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skills and experience and interest in data analysis, data science, machine learning and process automation would be an advantage. Previous experience with XAS or other synchrotron-based techniques would be
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using machine learning and deep learning techniques to generate indicators that allow remote monitoring of restoration. Knowledge of remote sensing (e.g. GEDI, LiDAR, multispectral) and programming (e.g
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modelling and machine learning applications in process industries; advanced process control (APC); model predictive control (MPC); digital twins and real-time process monitoring and control; process
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variables, fixed effects for panel data, matching estimators, or machine learning) or other advanced statistical modelling.- Advanced programming skills in Stata, R, Python or a similar software.- Strong
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at least statistical insights into the risks and success rates of real, patient-specific aneurysms, their treatment options, and long-term prognosis. The project is complemented by contributions in machine
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research group, apply for externally funded research as a principal investigator and teach. In addition: you must have completed all requirements of your doctorate or health professional degree no more than
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motivated PhD students, interns, and PostDocs at the intersection of computer vision and machine learning. The positions are fully-funded with payments and benefits according to German public service
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of Dr Benoit Gosselin (Université Laval), Guillaume Lajoie (UdeM) and Marco Bonizzato (Polytechnique). It integrates the use of machine-learning approaches to optimize neurostimulation, automation
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-to-system solutions to prepare and submit your application to Grants.gov and track your application in eRA Commons. Learn more . Table of Contents Part 1. Overview Information Part 2. Full Text