62 data-"https:" "https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" PhD scholarships at Technical University of Munich
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. Jörg Ott
More Information https://www.in.tum.de/fileadmin/w00bws/cm/jobs/2021-04-6g-job.pdf -
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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details of two referees The deadline for application is March 1st, 2026. For more information about PFT group, please check on our website Particle and Fiber Technology The position is suitable for disabled
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affect plant performance across environments. The project follows an integrated experi-mental approach across laboratory, greenhouse, and field scales, combined with advanced phenotyping and data-driven
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publications Letter of motivation, maximum 1 page Degree certificates and academic transcripts Contact details of two referees The deadline for application is March 1st , 2026. For more information about PFT
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imaging. Your Profile: The successful applicant must have the following: • Master’s degree in physics, biophysics, biomedical engineering, computer engineering or electrical engineering. • Excellent track
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preference in case of generally equivalent suitability, aptitude and professional performance. Data Protection Information: When you apply for a position with the Technical University of Munich (TUM), you are
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, Mechanical Engineering, Electrical Engineering, Computer Engineering, or a closely related discipline. Strong research interest in telerobotics, shared control, human–robot interaction, or networked control
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qualified women. About the position The position contains both teaching duties and participation in research projects. The research project topics focus on improving object recognition through computer vision