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, quantitative imaging, machine learning, and AI applications in radiology. The research area includes innovative work on developing Deep Learning Based Image reconstruction in CT on Photon Counting Detector
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without Centralized Training Data”, https://ai.googleblog.com/2017/04/federated-learning-collaborative.html [2] “Learning with Privacy at Scale”, https://machinelearning.apple.com/research/learning
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infrastructure for deep learning, speech, and audio research, including Aalto University’s large-scale scientific computing cluster with CPU and GPU nodes, access to CSC’s national computing infrastructure
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machine learning 2.Auto generation of code for HPC algorithms using empirical models based on machine learning. 3.Extreme speedup and scalability of deep learning: Achieve extreme scalability of deep
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Responsibilities: Develop and apply machine learning and deep learning models (e.g., graph neural networks, generative models, transfer learning) for materials property prediction, interpretation, and
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. Strong expertise in machine learning and deep learning, with demonstrated experience in one or more of the following areas: computer vision, markerless pose estimation, movement analysis, behavioural
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the development of computational pipelines and reproducible workflows for the analysis of biological and biomedical data using deep learning techniques; • promotion of technology transfer and support
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for structured data is particularly relevant to this position. Key qualifications include: Strong research experience in deep learning and foundation models, including experience with pre-trained
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years) Openings: Several Natural Intelligence (NISYS GmbH) , a newly founded deep-tech startup at the intersection of neuroscience and machine learning, invites applications for a Senior Research
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carried out at the Department of Information and Communications Engineering, DICE , at Aalto University, Finland. The project environment offers excellent infrastructure for deep learning, speech