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-supervised learning, and few/zero-shot techniques — the student will adapt models to ecological data. Bayesian deep learning and ensemble methods will be explored for trustworthy uncertainty estimation
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that shape our future. Fueled by curiosity and a deep sense of duty, they contribute invaluable insights to research and teaching, enriching our society. Are you inspired and driven by the desire to make a
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. This part of the project will be conducted in collaboration with MR Solutions Group. Axis 3 – Automated Generation of Attenuation Maps Using Deep Learning The use of AI for PET data correction has been
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artificial intelligence (i.e. machine, deep and reinforcement learning…) to optimize efficiency, improve safety, reduce costs and promote sustainability. Collaborate with multidisciplinary teams to uncover a
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) Deep Learning AI. https://www.deeplearning.ai/ (opens in new window) CourseRA Gen AI https://www.coursera.org/ (opens in new window) McKinney, S.M. et al., “International evaluation of an AI system
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of Sentinel-2 fluvial scenes’. Earth Surf. Process. Landforms, 45, 3120–3140. Carbonneau et al 2020) ‘Adopting deep learning methods for airborne RGB fluvial scene classification’. Remote Sensing of Environment
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to explore new analysis methods using deep learning. Depending on the interest, it is also possible to be involved in the wet lab. Professor Tiwari also leads the Center for Integrated Multiomics in Precision
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assessing deep learning models in ESRI ArcGIS Pro, or alternative approaches as appropriate). Work with international project collaborators to connect analyses with ground-penetrating radar investigations