30 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"FIIB-HUIS-HUHEN" PhD positions at Technical University of Munich
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12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5
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University of São Paulo, Brazil. This position focuses on developing advanced computer vision methods and hardware setup for detecting and predicting plant diseases in soybean cultivation. About Us The Chair
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11.11.2024, Academic staff In the project “BIG-ROHU” (BIG Data - Rotor Health and Usage Monitoring), a system is being developed which provides information on both the health and the actual stress
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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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research in the broad field of computational methods for the built environment. Particular emphasis is placed on building information modelling, digital drawings, point cloud capturing and processing as
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Regulation (GDPR)). By submitting your application, you confirm that you have acknowledged the above data protection information of TUM. Kontakt: shadi.albarqouni@helmholtz-muenchen.de More Information https
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. The project 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
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or interest in this position. General information and research topics of the Maaß-group can be found at www.maass.nu. The position is suitable for disabled persons. Disabled applicants will be given preference
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12.01.2026, Academic staff The Professorship of Machine Learning at the Department of Computer Engineering at TUM has an open position for a doctoral researcher (TV-L E13 100%; initial contract 1.5
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Chair of Biological Imaging 02.02.2026, Academic staff We are looking for a candidate (m/f/x) who will use the combination of our spectroscopy infrastructure, and structural information