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Field
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and analysis of mathematical methods for novel imaging techniques and foundations of machine learning. Within the project COMFORT (funded by BMFTR) we aim to develop new algorithms for the training
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reconstruction algorithms. Inconsistencies can be used to correct the input data, for example to improve attenuation correction. The aim of this postdoc is to correct rigid motion in SPECT reconstruction based
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build the sustainable companies and societies of the future. Subject description The research subject focuses on an integrated development of network architectures, resource efficient algorithms, and
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large quantities of data to gain a greater understanding of our systems and develop data analytics and artificial intelligence algorithms. You will be actively engaged in the research and development
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imaging with clinical text and decision support. Evaluate algorithms regarding robustness, explainability, and clinical impact in musculoskeletal medicine. Collaborate in an interdisciplinary team
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colorectal cancer screening and treatment. They will contribute to the design of AI algorithms for polyp detection, tissue characterization, and visual guidance of robotic intervention. This is a full time
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of the postdoctoral researcher will include: To work closely and proactively with Prof Anton van den Hengel to scope and develop research ideas. To develop algorithms, machine learning models, Python modules
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new globally accessible infrastructure and new algorithms for multimodal mining of biosynthetic diversity, as well as novel lead compounds that can be taken up by consortium partners to attain concrete
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on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems tailored to dynamic, human-centered environments. They may also work with diverse signal modalities, including vision
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5 Sep 2025 Job Information Organisation/Company CNRS Department Laboratoire d'Informatique, Signaux et Systèmes de Sophia Antipolis Research Field Computer science Mathematics » Algorithms