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Field
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deep learning techniques to improve image processing and trait prediction. Analyze large datasets generated by the Phenomobile.v2+ to identify key traits affecting crop performance under stress
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Electrical Engineering, Computer Science, or a related field Strong background in speech processing, signal processing or machine learning Proficiency in Python and deep learning frameworks Experience with far
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communication) Willingness to learn and confront new challenges Preferred Qualifications Doctoral research conducted in the area of machine learning for healthcare and related topics Deep knowledge of multi-modal
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-traditional, e.g., event data) and network structures (for sensor networks). In this project, we will investigate Bayesian deep learning approaches to training models under uncertainty for several sensing
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the intersection of machine learning and genomics. The project involves the development and application of advanced machine learning and deep learning techniques to understand the sequence-function relationships
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Electrical Engineering, Computer Science, or a related field Strong background in speech processing, signal processing or machine learning Proficiency in Python and deep learning frameworks Experience with far
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robust models – and for clinicians, whose goal is to determine when to trust the models. We therefore seek candidates who have strong technical background in working with large-scale deep learning models
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, computational, and machine learning/AI methods, with a particular emphasis on deep learning approaches improve our understanding and prediction of infectious disease dynamics. Projects are also strongly grounded
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supported by an external team of deep-learning experts. You will also become an integral part of the Multiscale Cloud Physics Group currently being established by Dr Franziska Glassmeier at the Max Planck
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scientists, and researchers working on medical image analysis, machine learning, and audiology. Our recent work has focused on using deep learning to analyse temporal bone CT scans and brain MRI data in