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26.03.2026, Academic staff Doctoral Candidate f/m/d in computational proteomics/bioinformatics with a focus on plant proteomics Candidates must hold a master´s degree in Data Engineering, Data
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that you have acknowledged the above data protection information of TUM. Kontakt: shadi.albarqouni@helmholtz-muenchen.de More Information https://albarqouni.github.io/team/
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19.07.2022, Academic staff The Machine Learning and Information Processing group at TUM works in the intersection of machine learning and signal/information processing with a current focus on deep
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focuses on developing information theory, coding schemes, and other algorithmic methods for DNA data storage. Here is a video on the topic: https://www.bbc.com/future/article/20151122-this-is-how-to-store
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the topic: “AI-based processing of CAD models for automated planning of computer-aided manufacturing.” The candidate has the opportunity to pursue a doctoral degree (Ph.D.). Remuneration is 100% TVL E13
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In modern and increasingly decentralized data ecosystems, the automated integration of heterogeneous systems plays a central role. The goal of this thesis is to automatically generate semantically
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and evaluation of innovative data-driven and Machine Learning-based systems to integrate more renewable energy into our energy systems and make energy use more efficient. We develop novel optimization
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. Research at the DKFZ is organized into the following programs with a lot of interaction and interdisciplinary PhD projects available across different topics: For more information about the groups and their
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PhD/Postdoc position in trustworthy data-driven control and networked AI for rehabilitation robotics
for sustainability, new concepts for security and solutions for current latencies in communication networks. Find out more about the project under https://6g-life.de/ About us: At the Chair of Information-Oriented
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test test The position is suitable for disabled persons. Disabled applicants will be given preference in case of generally equivalent suitability, aptitude and professional performance. Data Protection