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Helmholtz Zentrum München - Deutsches Forschungszentrum für Gesundheit und Umwelt | Stein bei N rnberg, Bayern | Germany | 12 days ago
the Fugger lab at the Oxford Centre of Neuroinflammation , focusing on the development of drugs that tame common brain diseases through the application of graph-based neural networks, deep learning, and
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The Singapore Institute of Technology (SIT) is Singapore’s first University of Applied Learning, offering industry-relevant degree programmes that prepare its graduates to be work- and future-ready professionals
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University of Applied Learning, offering industry-relevant degree programmes that prepare its graduates to be work- and future-ready professionals. Its mission is to maximise the potential of its learners and
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and memory, and with the design and implementation of cutting-edge data analysis pipelines that use deep learning to reconstruct perceived information from functional MRI in real time. For more
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at the interface of machine learning, deep learning, geospatial AI, causal modelling, and digital health systems. Your Role You will develop the core AI and data-driven models that transform large-scale
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Apply now Job no:502178 Work type:Part time Location:Hobart Categories:Teaching Intensive Shape future health leaders through innovative postgraduate teaching Deliver high-quality online learning
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., turbine components).Research on advanced deep learning techniques, including architectures based on GRU, LSTM, attention mechanisms, and hybrid models.Implementation of real-time predictive models (soft
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Job Requirement Have relevant competence in the areas of Deep Learning/Computer Vision. The experience in diffusion models is a plus. Have a PhD degree in computer science/engineering or related
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Framework Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description As a PhD candidate, you will: - Develop and train deep-learning
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implement computer vision pipelines for crop monitoring, plant stress detection, and disease identification in greenhouse environments. Apply machine learning and deep learning models (semantic segmentation