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PhD student (f/m/d) who wants to take ownership of the software ecosystem behind our computational imaging research – from experimental reconstruction algorithms used inside our lab to robust tools used
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foundations of medical deep learning. The project focuses on novel self-supervised objectives, information geometry, mitigating representation bias for rare pathological findings, and building next-generation
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a doctorate in artificial intelligence, medical informatics, and precision oncology? Then join the xMDT-HPB project at the Institute for AI and Informatics in Medicine (AIIM), a pioneering research
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be released as open-source software and reusable research artifacts. Your tasks: You will contribute to the clinical-informatics and AI workstream of SEQUORA: Co-design and implement the clinical
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involving Prof. Dr. Michael Bader (TUM CIT, Hardware-aware algorithms for HPC) , Prof. Dr. Felix Dietrich (TUM CIT, Physics-enhanced Machine Learning) , and Prof. Dr. Hartwig Anzt (TUM CIT, Computational
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information is contained in these data and develop the computational and statistical approaches needed to extract it. Working closely with experts in imaging technology, algorithm development, biology, and
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. ▪ Working closely with partners at TUD and theoretical researchers on algorithm development, performance analysis, implementation, and experimental validation. To be qualified for this position, you should
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theoretical and computational methods to describe electronic, optical, and transport properties of complex materials. The first advertised project (a) is dedicated to the methodological enhancement
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Top-ranked Master's degree in robotics, computer vision, system control, machine learning, mathematics, or a related field (background in any of the following); Being excited to make a real impact with
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biochemists developing the labeling agents, data analysts developing analysis algorithms and physicists developing hardware. The candidate The candidate should have a firm base in in vivo imaging and cell