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international and dynamic team of researchers investigating problems in information retrieval (IR) and natural language processing (NLP) and their applications to health and medicine. The successful candidate
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will focus on the design and implementation of advanced models for data enhancement, denoising, semantic segmentation, content-based retrieval, target detection, multitemporal analysis, and radar mapping
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judiciary Have experience with large language models, information retrieval, evaluation of ML systems, and deploying applications; this is highly desirable Have an excellent command of English; German
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reconstruction to overcome these challenges. Your tasks - develop physics-informed, self-supervised learning approaches for phase retrieval - implement reconstruction algorithms on HPC clusters for large-scale
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tomography and local adaptive reconstruction to overcome these challenges. Your tasks develop physics-informed, self-supervised learning approaches for phase retrieval implement reconstruction algorithms
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different skills, life experiences and perspectives to contribute to even better problem solving of our societal mission in research and education. If you think this position is relevant and interesting, we
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and Health Sciences https://www.ntnu.edu/studies/phmedhv Excellent oral and written communication skills in English ------------------ The appointment is to be made in accordance with Regulations
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conditions for research of high scientific quality with clear industrial relevance. Read more about the division here: https://liu.se/en/organisation/liu/isy/fs . For more information about ISY, click here
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). For more information about our work, please visit our webpage: https://liu.se/en/organisation/liu/isy/cvl . For more information about ISY, go to: https://liu.se/en/article/open-positions-at-isy
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values rest on credibility, trust and security. By having the courage to think freely and innovate, our actions together, large and small, contribute to a better world. We look forward to receiving your