31 10-phd-candidates-or-postdoctoral-researchers-in-machine-learning-and-deep-learning Postdoctoral positions
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the outcomes of SCC surgery. Job Responsibilities: As a PhD candidate, you'll focus on: Develop cutting-edge AI models: Train state-of-the-art deep learning models to segment SCC and healthy tissues using both
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Research, and Meta. Responsibilities: The Postdoctoral Fellows will be responsible for leading ongoing innovative research projects. Examples include: The development of probabilistic deep learning models
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of biosystems and for extracting knowledge from (vast) sets of biotech data. A core technology leveraged by researchers at the center is deep machine learning, targeting the development of innovative tools and
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deep learning methods with clinical impact. The project is highly interdisciplinary, and the successful candidate is expected to interact with clinical and industrial partners. Where to apply Website
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are seeking a postdoctoral researcher specializing in digital technologies and urban health. The successful candidate will develop innovative solutions based on the analysis of urban data (big data, IoT, GIS
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. The researcher is expected to have (i) strong machine learning skills to improve model performance and robustness, and (ii) exemplary passion and motivation to pursue multidisciplinary research at the intersection
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related field Demonstrated experience in interdisciplinary research and excellent digital literacy Strong interest in historical data, machine learning, data visualization, or digital hermeneutics Strong
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of recruiting talent aligned to these values. We are looking for a Postdoctoral Research Fellow who has: a PhD (or in near completion) in the relevant fields of Artificial Intelligence, Machine Learning, HCI
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expertise in analysing/ training models on biological or chemical datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep
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datasets Proficiency in Python for data science and machine learning Possess sufficient breadth or depth of specialist knowledge with deep learning architectures including generative models, particularly