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, stringent layout design rules demand new design automation solutions beyond the actual state-of-the-art. The proposed work plan focuses on the thorough exploration of innovative generative machine learning
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mass spectrometry and machine learning now allow us to unravel this “dark proteome.” This position aims to use state-of-the-art AI-guided proteomics and systems biology approaches to map protease
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machine learning. The position will involve working with different research groups in the Department of Computer Science at the University of Cambridge, UK. In this collaborative project, we will apply
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expert knowledge in a reusable format. Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Do you have a background in deep learning and computer vision? Are you
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proactively. Experience in design, prototyping, basic programming, AI and/or machine learning are a plus. International PhD candidates with scholarships below the applicable IND income standard (currently
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pathology applications, including the assessment of kidney biopsies. The innovative application of machine learning in clinical settings creates a vibrant and inspiring research environment. You will be part
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expert knowledge in a reusable format. Numerical Representation, Develop numerical representations of ship designs that are interpretable by machine learning algorithms and suitable for generative ai model
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Do you have a background in deep learning and computer vision? Are you independent, creative and eager to take initiatives? Do you enjoy working in an international research group and interacting
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theoretical analysis, implementation of methods in computer codes, use of state-of-the-art high-performance computers in Sweden and in Europe, application of machine-learning and AI techniques, and