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Area of research: Scientific / postdoctoral posts Job description: Postdoc (f/m/x) in Deep Learning and Digital Pathology 102827 Full time 39 hrs./week Neuherberg near Munich Partial Home Office
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. The appointees will participate in a multidisciplinary collaborative research project related to development of deep learning model for diagnosis and prognosis of different sarcomas. He/she will develop and train
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, and recommend personalised treatment for musculoskeletal conditions. Key skills will include deep learning, convolutional neural networks and transformers, multimodal AI and fusion modelling. Imaging
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for diagnosis and prognosis of different sarcomas. He/she will develop and train deep learning models with state-of-the-art algorithms based on histology whole slide images. They may also contribute to research
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, based on our recent deep learning biomechanics modelling work, you will perform cardiac biomechanical modelling to evaluate fetal heart function, to refine patient selection criteria for a fetal heart
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and development of perception stacks for autonomous mobile systems in general in any field Machine learning/deep learning experience applied to perception and any experience with deep Learning
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Inria, the French national research institute for the digital sciences | Paris 15, le de France | France | about 2 months ago
that diffusion models are a fundamental divergence from traditional deep learning paradigms. This suggests that existing generalisation theories are insufficient and highlights the need for a bespoke, algorithm
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often complex problems and opportunities that define our lives. Since our foundation in 1964, we have aspired to be a different type of university. Over the years, we have grown to become the centre of a
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/or spatial genomics, computational biology, machine learning, bioinformatics, and systems neuroscience. Prior experience with deep learning applied to biological data is a plus. Practical experience
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We are seeking to appoint a Senior Postdoctoral Researcher in Statistical Machine Learning and Deep Generative Modelling to apply and develop cutting-edge deep generative probabilistic models