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Training Group "AirMetro - Technological & Operational Integration of Highly Automated Air Transport in Urban Areas" (RTG 2947) , funded by the German Research Foundation (DFG). This interdisciplinary group
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processes that produce energy and raw materials. The Department of Radiation Research on Biological Systems is looking for a PhD Student (f/m/d) to investigate the impact of ionizing radiation on mammalian
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-management and conservation practices": PhD student (f,m,div) in the Field of Geodata, Nitrogen and Soil Parameter Modelling Reference number: 18/2025/4 The salary will be based on qualification and research
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Description The research group of Jun.-Prof. Dr. Johannes Walker welcomes applications for a Ph.D. position with a limited contract of three years according to the salary level E 13 TV-L (50 %). This position is to start at the earliest opportunity. The project will involved the development of...
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Description In the Leibniz Institute of Plant Biochemistry, the independent research group Receptor Biochemistry invites applications for a PhD position in (bio)chemistry (m/f/d) (Salary group E13
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Description The NHR Graduate School for HPC Talents 9 Ph.D. scholarships for HPC, Numerical Simulations, and AI/ML projects The NHR Graduate School seeks qualified applicants interested in pursuing a Ph.D. project in HPC, numerical simulation, and AI/ML. Fellows will receive a three-year...
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Description Within the IQST Graduate School framework, the hot atomic vapor spectroscopy group at the 5th Institute of Physics is currently seeking a PhD student. This PhD program is in close
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Description For our location in Hamburg we are seeking: PhD Position in Laser Plasma Acceleration Remuneration Group 13 | Limited: 3 years | Starting date: earliest possible | ID: MDO004/2025
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Description Are you interested in developing novel scientific machine learning models for a special class of ordinary and differential algebraic equations? We are currently looking for a PhD
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dynamics inherent in hydrological systems, offering a promising direction for integrating machine learning with physical modeling. The potential of neural ODE models in hydrology has been discussed in [3