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> on research projects related to kinetic equation and its related multiscale model reduction, numerical method, and data-driven/machine-learning approaches, including: • Numerical simulation of kinetic
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N2O from wetlands. We envisage combining process-based modelling and machine learning, as well as integration of Earth observation data into the modelling framework. The objective is to quantify the
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technical expertise in machine learning, artificial intelligence, and data modeling approaches. We are committed to investigating the mechanisms of brain aging and developing innovative interventions to
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research skillset in novel machine learning approaches, we are recruiting a team of outstanding researchers in cloud compute architecture design and event-triggered computing to work with us on
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scientific machine learning. More information about the department can be found at https://uwaterloo.ca/applied-mathematics/. Applications for these fellowships are through the website MathJobs.org
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machine/deep learning, computer vision, or applied statistics. Solid programming skills in Python and experience with deep learning frameworks (e.g., PyTorch or TensorFlow) Project funding Other Funding
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. Bioinformatics analysis of data will include use of population genomics techniques, phylogenetics and machine-learning development. The successful candidate will be expected to write up results as manuscripts
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will combine first-principles atomistic simulations, scientific machine learning, reaction modeling, and integration of computational and experimental data. The associate will develop reproducible
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ultimately shifts in species' distributions. This project harnesses research in ecological and agent-based modelling, machine learning, and AI to increase the predictive power of models of species
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functional and machine learning-derived features 4. Developing methods to characterize the genetic architecture of autism Salary and Benefits This position is salaried and benefits eligible