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dynamics, data science, and machine learning are beneficial. Please submit your detailed application with the usual documents by August 15, 2025 (stamped arrival date of the university central mail
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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
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expertise in the CRC-addressed PhD subjects, high interdisciplinary desire to learn and willingness to cooperate, openness for internationalization and diversity, very good verbal and written English
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disciplines strong analytical and methodological skills with a focus on quantitative data analysis (e.g., econometrics, statistics, machine learning) a high motivation and the ability to work independently with
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subsurface leaching into groundwater within agricultural systems experience in statistical analysis of research results or willingness to acquire such as well as to complete a PhD degree self-motivated
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learning and data analysis experts. The main tasks include the analysis of complex biomedical data using modern AI methods, as well as the development of novel machine and deep learning algorithms
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civil/electrical/control engineering or mathematics or related study programs with a solid basis in choice modelling and/or reinforcement learning, with knowledge of MATSim is advantageous. Description
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interdisciplinary desire to learn and willingness to cooperate, openness for internationalization and diversity, very good verbal and written English communication skills as well as the absolute determination
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research and teaching (§ 72 HessHG), while also advancing your professional and didactic qualifications. You will teach courses in "Animal Physiology" and "Neurobiology" and research the neuronal processing
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– from the modeling of material behavior to the development of the material to the finished component. PhD Position in Machine Learning and Computer Simulation Reference code: 50145735_2 – 2025/WD 1