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skills in machine learning, deep learning, and advanced statistics for processing complex data. Urban Health Principles: Familiarity with urban planning principles centered on health (active mobility
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. The appointee will primarily conduct research applying advanced machine learning/AI (including techniques like deep learning) to analyze complex biological and clinical data (e.g., single-cell multi-omics
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-based sensor data to enhance the prediction of peatland soil properties and functions. You will focus on leveraging machine learning/deep learning techniques along with explainable artificial intelligence
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equitable research environment that values diversity in all its forms. To learn more about ongoing research and recent publications, please visit: https://kaushiklab.com . Why MUN? The Faculty of Medicine
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on the training strategies. In this project, we will investigate Bayesian methods to train deterministic SNNs (with deterministic activation functions) or probabilistic SNNs. Bayesian deep learning methods have
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, and use deep learning to gain insight into biological processes. You will also gain direct exposure to cardiovascular physiology and rodent imaging in close collaboration with biologists. We work
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in research and development of sustainable energy conversion technologies. We are recognized as global leaders in this field, supported by state-of-the-art facilities and deep expertise. Our
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Measure Theory : Leveraging foundational mathematical frameworks to design robust modeling approaches. 2) Deep Learning : Exploring cutting-edge techniques such as multimodal data integration, diffusion
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: Automated tracking of ankle muscle fascicle kinematics in both superficial and deep muscles will allow for the intuitive and coordinated control of powered prostheses following leg amputations. In
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and sets up experiments in hybrid research environment. 2. Researches artificial intelligence/machine learning algorithms, database design, deep learning, big data, and cloud computing. 3. Publishes