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areas, could include deep learning (e.g. Long Short Term Memory - LSTM), statistical baselines (e.g. Autoregressive Integrated Moving Average - ARIMA, Kalman filters) and transformers (e.g., spatio
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higher degree students. What we’re looking for: A postgraduate qualification (Masters, PhD or equivalent) in a relevant field. Experience in University-level teaching and learning. Clinical/industry
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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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at appointment. See the following table for the salary scale for this position: https://www.ucop.edu/academic-personnel-programs/_files/2025-26/represented-july-2025-scales/t15.pdf . A reasonable estimate for this
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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
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learning , AI for Health Skills : Knowledge : Where to apply Website https://rubis.univ-spn.fr/offres/voir/195 Requirements Specific Requirements Master 2 en science des données Additional Information Work
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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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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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deep-rooted mindfulness for the natural world and all who depend on it, and together, we apply knowledge, tools and skills to build a better future for all. FACTS: • Top 1.4% university in the world
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opportunity to teach and mentor students who are eager to explore the dynamic world of sports journalism, broadcasting, and digital media. We are looking for an experienced sports media professional with a deep