168 data-"https:"-"https:"-"https:"-"https:"-"https:"-"https:"-"L2CM"-"L2CM" PhD positions in Germany
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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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Course language English and German Current information Application deadlines: 15 March and 15 September Financial support No Structured research and supervision Yes Research training / discussion Yes
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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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at the Institute of Medical Informatics within the research group “Medical Data Integration Center (MeDIC)” led by Dr. Michael Storck and is embedded in the DFG-funded Collaborative Research Centre 1748, Principles
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DIPF | Leibniz Institute for Research and Information in Education contributes to addressing challenges in education through empirical research, digital infrastructure and knowledge transfer. At its
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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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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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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