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PhD Scholarship in Multimodal Federated Learning and Medical Image Analysis Job No.: 695949 Location: Clayton campus Employment Type: Full-time Duration: 3-year and 3-month fixed-term appointment
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identity, or gender expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment is contingent upon the successful completion of a background
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your academic career? Your interests lie in the field of machine learning techniques, particularly artificial neural networks, and deep learning? And you would like to continue your research
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candidates will have experience in artificial intelligence, deep learning or decision support applied to RF sensing, wireless communications and signal processing. A strong background in multimodal data
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, Mathematics, Engineering or a related discipline, with an interest in AI applied to complex and safety-critical systems. Good knowledge of Machine Learning and Deep Learning methods, including experience with
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: Master’s degree in Electrical Engineering Ranked within the top 10% of their class in MSc and BSc, and have exceptional grades Good background in deep learning with familiarity in model training, inference
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and AI, including experience in machine learning software development. E3. Experience in training deep learning models relevant in research projects. E4. Experience of applying good software engineering
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genetic basis of plant–microbe interactions, with a particular emphasis on data integration across plant species and data types (genomics, transcriptomics). Design, adapt and use deep learning methods
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Inria, the French national research institute for the digital sciences | Grenoble, Rhone Alpes | France | 2 months ago
representations (IR) to bridge deep learning frameworks with low-level hardware, ensuring the seamless evolution of existing software infrastructures. Additionally, he will act as a high-level technical expert
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. Demonstrated success in developing innovative programs, strengthening teaching and learning outcomes, and expanding industry partnerships. Deep knowledge of at least one of the School's disciplines, with strong